Course Code: CSE 1213-0613

Course Title: Structured Programming Language

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course focuses on the syntax and semantics of structured programming while analyzing and designing various programming problems using different libraries and user-defined functions. Also, it helps to develop basic programming and problem-solving skills to program design and development.

Course Contents:

1. Fundamental of structured Programming: Main () method, Program structure, Primitive Data Types, Variables, Constants, Assignments, Initializations, preprocessor, compiler, interpreter, IDE

2. Flowchart: Flowchart design, algorithm design for problem solving, pseudocode

3. Keywords and library functions: Uses of all keywords, descriptions,s and code examples

4. Control statement: if-else, switch case, ternary operator, break, code examples

5. Loop: For loop, while loop, do-while loop, nested loop, for each loop, auto keyword

6. Function: Declaration, return type, argument, pointer argument

7. Recursion: Basic codes with recursion, base case, and types of recursions: linear, tail, binary, nested, mutual

8. Array and String: Declaration, Traversing, character array, sizeof(), strcat(), strcmp(), strcpy(), getline()

9. 2D array and Pointer: 2D array declaration and operation, address, reference, dereference, pointer arithmetic

10. Struct and memory alignment: Definition, access member functions, typedef, structure within a structure, memory alignment issue

11. File IO: Types of files, File operation: create, open, close, reading, the file pointer

12. Dynamic memory allocation: auto variables, malloc(), calloc(), free(), realloc(), pointer and address

13. Bitwise Manipulation: Memory layout, Bitwise operators: AND(&), OR(|), XOR(^), NOT (~), LEFT SHIFT(<<), RIGHT SHIFT(>>), Bit field

Course Learning Outcomes (CLOs):

CLO1: Able to know the basics of programming, syntax, keyword, function, and structures.

CLO2: Able to identify the typical characteristics of problems and mechanisms to solve problems utilizing programming knowledge.

CLO3: Able to design and develop programming solutions after real-life problem investigation.

CLO4: Competent to apply relevant advanced tools and predict the solutions to problems of contemporary technologies.

References:

Learning Materials:

Textbooks:

1. The C Programming Language. 2nd Edition Book, Brian Kernighan and Dennis Ritchie

2. Teach yourself c by herbert schildt

3. Competitive Programmer’s Handbook, Antti Laaksonen

Other learning materials: Journals, Web Materials, etc.

Course Title: Structured Programming Language

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course focuses on the syntax and semantics of structured programming while analyzing and designing various programming problems using different libraries and user-defined functions. Also, it helps to develop basic programming and problem-solving skills to program design and development.

Course Contents:

1. Fundamental of structured Programming: Main () method, Program structure, Primitive Data Types, Variables, Constants, Assignments, Initializations, preprocessor, compiler, interpreter, IDE

2. Flowchart: Flowchart design, algorithm design for problem solving, pseudocode

3. Keywords and library functions: Uses of all keywords, descriptions,s and code examples

4. Control statement: if-else, switch case, ternary operator, break, code examples

5. Loop: For loop, while loop, do-while loop, nested loop, for each loop, auto keyword

6. Function: Declaration, return type, argument, pointer argument

7. Recursion: Basic codes with recursion, base case, and types of recursions: linear, tail, binary, nested, mutual

8. Array and String: Declaration, Traversing, character array, sizeof(), strcat(), strcmp(), strcpy(), getline()

9. 2D array and Pointer: 2D array declaration and operation, address, reference, dereference, pointer arithmetic

10. Struct and memory alignment: Definition, access member functions, typedef, structure within a structure, memory alignment issue

11. File IO: Types of files, File operation: create, open, close, reading, the file pointer

12. Dynamic memory allocation: auto variables, malloc(), calloc(), free(), realloc(), pointer and address

13. Bitwise Manipulation: Memory layout, Bitwise operators: AND(&), OR(|), XOR(^), NOT (~), LEFT SHIFT(<<), RIGHT SHIFT(>>), Bit field

Course Learning Outcomes (CLOs):

CLO1: Able to know the basics of programming, syntax, keyword, function, and structures.

CLO2: Able to identify the typical characteristics of problems and mechanisms to solve problems utilizing programming knowledge.

CLO3: Able to design and develop programming solutions after real-life problem investigation.

CLO4: Competent to apply relevant advanced tools and predict the solutions to problems of contemporary technologies.

References:

Learning Materials:

Textbooks:

1. The C Programming Language. 2nd Edition Book, Brian Kernighan and Dennis Ritchie

2. Teach yourself c by herbert schildt

3. Competitive Programmer’s Handbook, Antti Laaksonen

Other learning materials: Journals, Web Materials, etc.

Course Code: CSE 1214-0613

Course Title: Structured Programming Language Lab

Course Type: Lab

Prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course focuses on the syntax, and semantics of structured programming while analyzing and designing various applications using different library functions. Also, it helps to develop basic programming and problem-solving skills to program design and development.

Laboratory Tasks:

➢ Practice with the Basic Structure of a C Program

➢ Control the C Program Development Environment

➢ Write program Constants, Variable & Data Types, ASCII Table

➢ Write Program using Operators & Expressions in C Operator Precedence & Associativity

➢ Write program to Manage I/O Operations in C

➢ Write sample program using Bitwise Operator and Signed Unsigned Data Type

➢ Program for Decision Making Statements(if, if else, else if ladder, nested if, switch)

➢ Program for Looping Statements(for, while, do..while)

➢ Program for Jump Statements (continue, break, goto)

➢ Practice using Function

➢ Practice with Array

➢ 1D Array & its Memory Representations

➢ 2D Array & its Memory Representations

➢ Matrix Operations using Array

➢ Passing Arrays to Functions

➢ Practice with Pointer

➢ Dynamic Memory Allocation Programming

➢ Programming with Structure and Union

➢ File Processing Project using Pointer

➢ Basic Graphics Programming Practice

Course Learning Outcomes (CLOs):

CLO1: Understand the basics of structured programming, keywords, and syntax.

CLO2: Understand typical characteristics, and mechanisms and solve problems using a structured programming language.

CLO3: Develop basic programming skills with respect to program design and development.

References:

Learning Materials:

Textbooks:

1. The C Programming Language. 2nd Edition Book, Brian Kernighan and Dennis Ritchie

2. Teach yourself c by Herbert Schildt

3. Competitive Programmer’s Handbook, Antti Laaksonen

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Structured Programming Language Lab

Course Type: Lab

Prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course focuses on the syntax, and semantics of structured programming while analyzing and designing various applications using different library functions. Also, it helps to develop basic programming and problem-solving skills to program design and development.

Laboratory Tasks:

➢ Practice with the Basic Structure of a C Program

➢ Control the C Program Development Environment

➢ Write program Constants, Variable & Data Types, ASCII Table

➢ Write Program using Operators & Expressions in C Operator Precedence & Associativity

➢ Write program to Manage I/O Operations in C

➢ Write sample program using Bitwise Operator and Signed Unsigned Data Type

➢ Program for Decision Making Statements(if, if else, else if ladder, nested if, switch)

➢ Program for Looping Statements(for, while, do..while)

➢ Program for Jump Statements (continue, break, goto)

➢ Practice using Function

➢ Practice with Array

➢ 1D Array & its Memory Representations

➢ 2D Array & its Memory Representations

➢ Matrix Operations using Array

➢ Passing Arrays to Functions

➢ Practice with Pointer

➢ Dynamic Memory Allocation Programming

➢ Programming with Structure and Union

➢ File Processing Project using Pointer

➢ Basic Graphics Programming Practice

Course Learning Outcomes (CLOs):

CLO1: Understand the basics of structured programming, keywords, and syntax.

CLO2: Understand typical characteristics, and mechanisms and solve problems using a structured programming language.

CLO3: Develop basic programming skills with respect to program design and development.

References:

Learning Materials:

Textbooks:

1. The C Programming Language. 2nd Edition Book, Brian Kernighan and Dennis Ritchie

2. Teach yourself c by Herbert Schildt

3. Competitive Programmer’s Handbook, Antti Laaksonen

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CHE- 1112-0531

Course Title: Chemistry

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hour: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

Chemistry is the study of materials and substances, and the transformations they undergo through interactions and the transfer of energy. Chemistry develops students’ understanding of the key chemical concepts and models of structure, bonding, and chemical change, including the role of chemical, electrical and thermal energy. Students learn how models of structure and bonding enable chemists to predict properties and reactions and to adapt these for particular purposes. Students design and conduct qualitative and quantitative investigations both individually and collaboratively. They investigate questions and hypotheses, manipulate variables, analyze data, evaluate claims, solve problems and develop and communicate evidence-based arguments and models. The study of chemistry provides a foundation for undertaking investigations in a wide range of scientific fields and often provides a unifying link across interdisciplinary studies.

Course Contents:

1. Periodicity of the Elements: Mendeleev’s periodic law and the periodic table, Distribution of electrons in the atoms of elements, Pauli

2. Exclusion Principle, Aufbau principle, Heisenberg uncertainty principle, Hund's rule. Writing electron configuration using the periodic table, some periodic properties such as Atomic and Ionic radii, Ionization potential, and Electron affinity.

3. Chemical Bonding: Electronic theory of chemical bond, Nature of covalent bond, Valence bond theory (VBT), Molecular Orbital theory (MOT), Bond order or bond multiplicity.

4. Complex Compounds: Types of ligands, Sidgwick theory, Effective atomic number, Werner theory, Crystal field theory, structure, isomerism, and applications.

5. Acid and Bases: Various concepts of acid and bases, Neutralization reaction, Strength of acid and bases, Hard and soft acid and bases, Acid bases properties of oxides, hydroxides and salts, and Effect of structure on acid bases properties.

6. Analytical Chemistry: Instrumental methods and their classification, Advantage of instrumental method & Chemical method, Limitations of instrumental method & Chemical method, Sampling, Precision and accuracy, Mean and median, Types of error, Significant figure convention.

7. Theory of Dilute Solution: Colligative properties, lowering of vapor pressure, Elevation of boiling point, Depression of Freezing point, Osmosis and osmotic Pressure, Deduction of their formula and molecular weight from Raoult's law and their experimental determination.

8. Chemical Equilibrium: Law of mass action, Equilibrium constant, Application of the law of mass action to some chemical reaction, Heterogeneous equilibrium, Le-chatelier principle and its application to industrial reactions.

9. Chemical Kinetics: Rate of reaction, order and molecularity, zero order reaction, 1st and 2nd order reaction with its mathematical formulation, Determination of order of reaction, Effect of temperature on the rate of reaction. Theories of chemical reaction rate, Activation Energy, Activation complex, etc.

10. Colloids and Colloidal Solution: Classification preparation and purification, Properties, Protective action, and application of colloids. Emulsion, Types of emulsion, Role of emulsion.

11. Photochemistry: Laws of photochemistry, Quantum yield, Decomposition of hydrogen halide, photosensitized reaction, Fluorescence and phosphorescence, Luminescence, and Chemiluminescence.

References:

Learning Materials:

Textbooks:

1. Chemistry, Third Edition, Thomas R Gilbert, Rein V Kirss, Natalie Foster and Davies.

2. Chemistry, Second Edition, Gilbert, Kirss, Foster, and Davies.

3. Chemistry an Atoms-Focused Approach, Third Edition, Thomas R Gilbert, Rein V Kirss, Natalie Foster and Stacey Lowery Bretz.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Chemistry

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hour: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

Chemistry is the study of materials and substances, and the transformations they undergo through interactions and the transfer of energy. Chemistry develops students’ understanding of the key chemical concepts and models of structure, bonding, and chemical change, including the role of chemical, electrical and thermal energy. Students learn how models of structure and bonding enable chemists to predict properties and reactions and to adapt these for particular purposes. Students design and conduct qualitative and quantitative investigations both individually and collaboratively. They investigate questions and hypotheses, manipulate variables, analyze data, evaluate claims, solve problems and develop and communicate evidence-based arguments and models. The study of chemistry provides a foundation for undertaking investigations in a wide range of scientific fields and often provides a unifying link across interdisciplinary studies.

Course Contents:

1. Periodicity of the Elements: Mendeleev’s periodic law and the periodic table, Distribution of electrons in the atoms of elements, Pauli

2. Exclusion Principle, Aufbau principle, Heisenberg uncertainty principle, Hund's rule. Writing electron configuration using the periodic table, some periodic properties such as Atomic and Ionic radii, Ionization potential, and Electron affinity.

3. Chemical Bonding: Electronic theory of chemical bond, Nature of covalent bond, Valence bond theory (VBT), Molecular Orbital theory (MOT), Bond order or bond multiplicity.

4. Complex Compounds: Types of ligands, Sidgwick theory, Effective atomic number, Werner theory, Crystal field theory, structure, isomerism, and applications.

5. Acid and Bases: Various concepts of acid and bases, Neutralization reaction, Strength of acid and bases, Hard and soft acid and bases, Acid bases properties of oxides, hydroxides and salts, and Effect of structure on acid bases properties.

6. Analytical Chemistry: Instrumental methods and their classification, Advantage of instrumental method & Chemical method, Limitations of instrumental method & Chemical method, Sampling, Precision and accuracy, Mean and median, Types of error, Significant figure convention.

7. Theory of Dilute Solution: Colligative properties, lowering of vapor pressure, Elevation of boiling point, Depression of Freezing point, Osmosis and osmotic Pressure, Deduction of their formula and molecular weight from Raoult's law and their experimental determination.

8. Chemical Equilibrium: Law of mass action, Equilibrium constant, Application of the law of mass action to some chemical reaction, Heterogeneous equilibrium, Le-chatelier principle and its application to industrial reactions.

9. Chemical Kinetics: Rate of reaction, order and molecularity, zero order reaction, 1st and 2nd order reaction with its mathematical formulation, Determination of order of reaction, Effect of temperature on the rate of reaction. Theories of chemical reaction rate, Activation Energy, Activation complex, etc.

10. Colloids and Colloidal Solution: Classification preparation and purification, Properties, Protective action, and application of colloids. Emulsion, Types of emulsion, Role of emulsion.

11. Photochemistry: Laws of photochemistry, Quantum yield, Decomposition of hydrogen halide, photosensitized reaction, Fluorescence and phosphorescence, Luminescence, and Chemiluminescence.

References:

Learning Materials:

Textbooks:

1. Chemistry, Third Edition, Thomas R Gilbert, Rein V Kirss, Natalie Foster and Davies.

2. Chemistry, Second Edition, Gilbert, Kirss, Foster, and Davies.

3. Chemistry an Atoms-Focused Approach, Third Edition, Thomas R Gilbert, Rein V Kirss, Natalie Foster and Stacey Lowery Bretz.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CHE- 1112-0532

Course Title: Chemistry Lab

Course Type: Lab

Prerequisite: N/A

Credits: 1

Contact Hour: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

The main focus of this course is to understand and analyze different elements and their reactions to fire, acids, and bases. It also focuses on the preparations of acids, bases, and inorganic compounds into different percentages.

Experiments:

Qualitative Analysis:

Dry test for acid radicals

Wet test for basic radicals

Preparation of stock solution & wet test for acid radicals

Separation of groups I, II, IIIA, IIIB, IV, V.

Analysis of group I (Pb, Ag, Hg)

Analysis of group II (Pb, Cu, Cd, Hg, Sb, Sn)

Analysis of group IIIA (Al, Fe, Cr)

Analysis of group IIIB (Co, Ni, Zn, Mn)

Analysis of group IV (Ca, Ba, Sr)

Analysis of group V (Mg, Na, K, NH4 +)

Volumetric Analysis

Preparation of 1M HCl and standardization

Preparation of 1M NaOH and standardization

Conversion of 98% H2SO4 or 37% HCl into suitable concentration.

Preparation of 1M H2SO4 and standardization.

Preparation of 1M CH3COOH and standardization.

Preparation of 1M KOH and standardization.

Inorganic Preparation

Preparation of Potassium dichromate

Preparation of Chrome Alum

Preparation of Ferrous Ammonium Sulfate

Preparation of Potassium Permanganate

Variation of pH of the different solutions (Acidic, Basic, Neutral)

Course Learning Outcomes (CLOs):

CLO1: Able to understand and analyze different elements from the periodic table.

CLO2: Able to prepare different acids, bases, and inorganic compounds into different ratios.

CLO3: Able to calculate mole ratios for preparing different compounds.

Course Title: Chemistry Lab

Course Type: Lab

Prerequisite: N/A

Credits: 1

Contact Hour: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

The main focus of this course is to understand and analyze different elements and their reactions to fire, acids, and bases. It also focuses on the preparations of acids, bases, and inorganic compounds into different percentages.

Experiments:

Qualitative Analysis:

Dry test for acid radicals

Wet test for basic radicals

Preparation of stock solution & wet test for acid radicals

Separation of groups I, II, IIIA, IIIB, IV, V.

Analysis of group I (Pb, Ag, Hg)

Analysis of group II (Pb, Cu, Cd, Hg, Sb, Sn)

Analysis of group IIIA (Al, Fe, Cr)

Analysis of group IIIB (Co, Ni, Zn, Mn)

Analysis of group IV (Ca, Ba, Sr)

Analysis of group V (Mg, Na, K, NH4 +)

Volumetric Analysis

Preparation of 1M HCl and standardization

Preparation of 1M NaOH and standardization

Conversion of 98% H2SO4 or 37% HCl into suitable concentration.

Preparation of 1M H2SO4 and standardization.

Preparation of 1M CH3COOH and standardization.

Preparation of 1M KOH and standardization.

Inorganic Preparation

Preparation of Potassium dichromate

Preparation of Chrome Alum

Preparation of Ferrous Ammonium Sulfate

Preparation of Potassium Permanganate

Variation of pH of the different solutions (Acidic, Basic, Neutral)

Course Learning Outcomes (CLOs):

CLO1: Able to understand and analyze different elements from the periodic table.

CLO2: Able to prepare different acids, bases, and inorganic compounds into different ratios.

CLO3: Able to calculate mole ratios for preparing different compounds.

Course Code: MATH-1111-0541

Course Title: Mathematics- I

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

Calculus and geometry are the basics of all Mathematical Sciences. It provides fundamental knowledge of differentiation and integration and also the formation of geometrical configurations. This course is designed to provide theoretical knowledge regarding limit and continuity, differentiation, extreme values, integrations, and geometrical configurations in two and three dimensions like straight lines, circles, planes, spheres, and cylinders.

Course Contents:

1. Differential Calculus: Fundamental of differentiation, Function, Limit and Continuity, differentiability, Differentiation, Successive differentiation, Partial differentiation, Leibnitz’s theorem, Euler’s theorem Maximum and minimum, Tangents and normal in Cartesian and Polar, Indeterminate forms, Curvature, Asymptotes, and Envelopes.

2. Expansions of functions: Rolle's theorem, Mean value theorem, Taylor's and Maclaurin’s theorems.

3. Indefinite and definite integrals: Fundamental of integrations, Indefinite integral by different methods, Definite integrals, and their properties; Walli’s formula, Reduction theorem, Multiple Integrals. Improper Integrals, Infinite integrals, Gamma and Beta functions,

4. Improper Integrals of the first kind and second kinds of Multiple Integrals.

5. Applications of proper and improper integrals: Determination of Area, Are lengths, the volume of solids of revolutions, Intrinsic equation in Cartesian and polar coordinate.

6. Coordinate Geometry in two dimensions: Change of axes, Pair of straight lines, General equation of second degree, Equations of circles, Parabola, ellipse and hyperbola, Tangent, Normal, Chord of contact, Pole and Polar, Conjugate point, Orthogonality, Radical axis, and Coaxial circles.

7. Coordinate Geometry in three dimensions: Coordinate systems- Direction cosines, Direction ratios, and Projections; Equations of straight lines, planes, spheres, and cylinders.

Course Learning Outcomes (CLOs):

At the end of the course, the student will be able to-

CLO1: Understand the fundamentals of differential and integral calculus and coordinate geometry.

CLO2: Analyze and sketch functions, lines, circles, parabolas, ellipses, planes, and spheres.

CLO3: Compute the rate of changes of functions, the origin of functions, lines, circles, Parabola, etc.

CLO4: Determine cost and profit, extreme values, area and volume, lines, circles, Parabola, etc.

CLO5: Apply calculus and geometry in solving engineering problems.

References:

Learning Materials:

Textbooks:

1. Howard Anton, Iril Bivens & Stephen Davis, 2012, Calculus, 10thed, Laurie Rosatone, USA

2. Das & Mukherjee. 1998. Differential Calculus, 4thed, U. N. Dhar & Sons Private Ltd., Kolkata.

3. Das and Mukherjee. 1996. Integral Calculus, 44thed, U. N. Dhar & Sons Ltd., Kolkata.

4. Thomas & Finny. 1996. Calculus and Analytic Geometry, 6thed, Norasa publishing house, London.

5. Rahaman & Bhattacharjee. 2002. Co-ordinate Geometry (two & three dimensions) with Vector Analysis, 12thed, S. Bhattacharjee, Dhaka

6. Bell, J. T. 1944. A Treatise on 3-Dimensional Geometry, 3rded, S.G. W. M., New Delhi

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Mathematics- I

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

Calculus and geometry are the basics of all Mathematical Sciences. It provides fundamental knowledge of differentiation and integration and also the formation of geometrical configurations. This course is designed to provide theoretical knowledge regarding limit and continuity, differentiation, extreme values, integrations, and geometrical configurations in two and three dimensions like straight lines, circles, planes, spheres, and cylinders.

Course Contents:

1. Differential Calculus: Fundamental of differentiation, Function, Limit and Continuity, differentiability, Differentiation, Successive differentiation, Partial differentiation, Leibnitz’s theorem, Euler’s theorem Maximum and minimum, Tangents and normal in Cartesian and Polar, Indeterminate forms, Curvature, Asymptotes, and Envelopes.

2. Expansions of functions: Rolle's theorem, Mean value theorem, Taylor's and Maclaurin’s theorems.

3. Indefinite and definite integrals: Fundamental of integrations, Indefinite integral by different methods, Definite integrals, and their properties; Walli’s formula, Reduction theorem, Multiple Integrals. Improper Integrals, Infinite integrals, Gamma and Beta functions,

4. Improper Integrals of the first kind and second kinds of Multiple Integrals.

5. Applications of proper and improper integrals: Determination of Area, Are lengths, the volume of solids of revolutions, Intrinsic equation in Cartesian and polar coordinate.

6. Coordinate Geometry in two dimensions: Change of axes, Pair of straight lines, General equation of second degree, Equations of circles, Parabola, ellipse and hyperbola, Tangent, Normal, Chord of contact, Pole and Polar, Conjugate point, Orthogonality, Radical axis, and Coaxial circles.

7. Coordinate Geometry in three dimensions: Coordinate systems- Direction cosines, Direction ratios, and Projections; Equations of straight lines, planes, spheres, and cylinders.

Course Learning Outcomes (CLOs):

At the end of the course, the student will be able to-

CLO1: Understand the fundamentals of differential and integral calculus and coordinate geometry.

CLO2: Analyze and sketch functions, lines, circles, parabolas, ellipses, planes, and spheres.

CLO3: Compute the rate of changes of functions, the origin of functions, lines, circles, Parabola, etc.

CLO4: Determine cost and profit, extreme values, area and volume, lines, circles, Parabola, etc.

CLO5: Apply calculus and geometry in solving engineering problems.

References:

Learning Materials:

Textbooks:

1. Howard Anton, Iril Bivens & Stephen Davis, 2012, Calculus, 10thed, Laurie Rosatone, USA

2. Das & Mukherjee. 1998. Differential Calculus, 4thed, U. N. Dhar & Sons Private Ltd., Kolkata.

3. Das and Mukherjee. 1996. Integral Calculus, 44thed, U. N. Dhar & Sons Ltd., Kolkata.

4. Thomas & Finny. 1996. Calculus and Analytic Geometry, 6thed, Norasa publishing house, London.

5. Rahaman & Bhattacharjee. 2002. Co-ordinate Geometry (two & three dimensions) with Vector Analysis, 12thed, S. Bhattacharjee, Dhaka

6. Bell, J. T. 1944. A Treatise on 3-Dimensional Geometry, 3rded, S.G. W. M., New Delhi

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: PHY-1111-0533

Course Title: Physics

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

This course is designed to meet the requirement of the basic knowledge of waves, optics, and thermal physics for Engineering students which is essential for understanding a wide range of physical phenomena including wave properties of matter, light, thermodynamics, and hydrodynamics. This course provides an outline of important phenomena in physics which comprises waves and oscillations, interference, diffraction, polarization, kinetic interpretation of heat, laws of thermodynamics, Carnot’s theorem, fluid mechanics, etc. This course is useful for fields and waves, renewable energy and optical communication, Biomedical Engineering, etc.

Course contents:

1. Waves and oscillations: Differential equation of simple harmonic oscillator, total energy, and average energy, a combination of simple harmonic oscillations, spring-mass system, torsional pendulum; two body oscillation, reduced mass, damped oscillation, forced oscillation, resonance, Progressive wave, power and intensity of wave, stationary wave, group, and phase velocities.

2. Interference of light: Young's double slit experiment, displacement of fringes and its uses, Fresnel bi-prism, interference in thin films, Newton's rings, interferometers.

3. Diffraction: Diffraction by a single slit, diffraction from a circular aperture, resolving power of optical instruments, diffraction at double slit and N-slits, diffraction grating.

4. Polarization: Production and analysis of polarized light, Brewster's law, Malus law, polarization by double refraction, Nicol prism, optical activity, Polarimeters.

5. Optical Defects: Defects of images: spherical aberration, astigmatism, coma, distortion, curvature, Chromatic aberration, and Theories of light.

6. Thermal Physics: Heat and work, the first law of thermodynamics and its applications; Carnot’s cycle, the second law of thermodynamics, Carnot's theorem, entropy.

7. The velocity of Sound and Vibration: Velocity of longitudinal waves in a gaseous medium, the velocity of sound in liquids, the velocity of sound waves in isotropic solids, transverse waves along a stretched string, laws of transverse vibration of a stretched string, Doppler effect, calculation of apparent frequency, the intensity of sound, limits of audibility, architectural acoustics.

8. Hydrodynamics: Laminar and turbulent flow, Equation of continuity, Reynolds number & its significance, Bernoulli's theorem and its application.

9. Viscosity: Newton’s law of viscous flow, Motion in a viscous medium-Stokes’ law, Determination of coefficient of viscosity.

10. Surface tension: Surface tension as a molecular phenomenon.

11. Kinetic Theory of gasses- Kinetic interpretation of temperature, specific heats of ideal gasses, equipartition of energy, mean free path, Maxwell's distribution of molecular speeds, reversible and irreversible processes.

Course Learning Outcomes (CLOs):

At the end of the course, the student will be able to-

CLO1: Identify and define important physical phenomena involved with basic principles of waves, heat, sound, optics, and fluids.

CLO2: Explain laws of physics associated with hydrodynamics, thermodynamics, propagation of light waves, and sound waves.

CLO3: Apply fundamental knowledge of physical laws and theories to solve different types of analytical problems.

CLO4: Analyze complex physical problems using the kinetic theory of gases, theories of light, sound, fluid mechanics, and thermodynamics.

References:

Textbooks:

1. Dr. Gias Uddin Ahmad “Physics for Engineers (Part-I)”

2. D. Halliday, R. Resnick, and J. Walker, "Fundamentals of Physics", 10th Edition, Extended.

3. Dr. Tafazzal Hossain “Waves and Oscillations” 2nd ed. B. Lal and N. Subrahmanyam, "Properties of Matter."

Other Learning Materials: Journals, Website Materials, YouTube Videos, etc.

Course notes, tutorial problems, and solutions can be accessed from the Google Classroom course module.

Course Title: Physics

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

This course is designed to meet the requirement of the basic knowledge of waves, optics, and thermal physics for Engineering students which is essential for understanding a wide range of physical phenomena including wave properties of matter, light, thermodynamics, and hydrodynamics. This course provides an outline of important phenomena in physics which comprises waves and oscillations, interference, diffraction, polarization, kinetic interpretation of heat, laws of thermodynamics, Carnot’s theorem, fluid mechanics, etc. This course is useful for fields and waves, renewable energy and optical communication, Biomedical Engineering, etc.

Course contents:

1. Waves and oscillations: Differential equation of simple harmonic oscillator, total energy, and average energy, a combination of simple harmonic oscillations, spring-mass system, torsional pendulum; two body oscillation, reduced mass, damped oscillation, forced oscillation, resonance, Progressive wave, power and intensity of wave, stationary wave, group, and phase velocities.

2. Interference of light: Young's double slit experiment, displacement of fringes and its uses, Fresnel bi-prism, interference in thin films, Newton's rings, interferometers.

3. Diffraction: Diffraction by a single slit, diffraction from a circular aperture, resolving power of optical instruments, diffraction at double slit and N-slits, diffraction grating.

4. Polarization: Production and analysis of polarized light, Brewster's law, Malus law, polarization by double refraction, Nicol prism, optical activity, Polarimeters.

5. Optical Defects: Defects of images: spherical aberration, astigmatism, coma, distortion, curvature, Chromatic aberration, and Theories of light.

6. Thermal Physics: Heat and work, the first law of thermodynamics and its applications; Carnot’s cycle, the second law of thermodynamics, Carnot's theorem, entropy.

7. The velocity of Sound and Vibration: Velocity of longitudinal waves in a gaseous medium, the velocity of sound in liquids, the velocity of sound waves in isotropic solids, transverse waves along a stretched string, laws of transverse vibration of a stretched string, Doppler effect, calculation of apparent frequency, the intensity of sound, limits of audibility, architectural acoustics.

8. Hydrodynamics: Laminar and turbulent flow, Equation of continuity, Reynolds number & its significance, Bernoulli's theorem and its application.

9. Viscosity: Newton’s law of viscous flow, Motion in a viscous medium-Stokes’ law, Determination of coefficient of viscosity.

10. Surface tension: Surface tension as a molecular phenomenon.

11. Kinetic Theory of gasses- Kinetic interpretation of temperature, specific heats of ideal gasses, equipartition of energy, mean free path, Maxwell's distribution of molecular speeds, reversible and irreversible processes.

Course Learning Outcomes (CLOs):

At the end of the course, the student will be able to-

CLO1: Identify and define important physical phenomena involved with basic principles of waves, heat, sound, optics, and fluids.

CLO2: Explain laws of physics associated with hydrodynamics, thermodynamics, propagation of light waves, and sound waves.

CLO3: Apply fundamental knowledge of physical laws and theories to solve different types of analytical problems.

CLO4: Analyze complex physical problems using the kinetic theory of gases, theories of light, sound, fluid mechanics, and thermodynamics.

References:

Textbooks:

1. Dr. Gias Uddin Ahmad “Physics for Engineers (Part-I)”

2. D. Halliday, R. Resnick, and J. Walker, "Fundamentals of Physics", 10th Edition, Extended.

3. Dr. Tafazzal Hossain “Waves and Oscillations” 2nd ed. B. Lal and N. Subrahmanyam, "Properties of Matter."

Other Learning Materials: Journals, Website Materials, YouTube Videos, etc.

Course notes, tutorial problems, and solutions can be accessed from the Google Classroom course module.

Course Code: 1112-0533

Course Title: Physics Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

A Physics lab is very important to learn the relevance between the theory and real solutions. This course will teach the students to implement and prove different types of Physics laws and rules and they will learn about how to be patient and careful during observation and calculation. Students will acquire knowledge about the application of Physics to get an elaborate idea of the rules and equations.

Experiments:

1. Verification of Ohm’s Law.

2. Calculating Young’s Modulus of a wire using the Vernier scale.

3. Determination of the value of the Acceleration due to Gravity(g) with the help of a compound(bar) pendulum.

4. Determination of the gravitational acceleration (g) by using a simple pendulum and verification of the formula.

5. Determination of the spring constant and effective mass of a given spiral spring.

6. Investigate the characteristics of series DC circuits and verify Kirchhoff's Voltage Law (KVL).

7. Determination of the radius of the curvature of a plano-convex lens by Newton’s rings method.

8. Determination of Young’s modulus of the given material bar by non-uniform bending using the pin and microscope method.

9. Determination of the moment of inertia of a given disc using a Torsion pendulum by the method of oscillations (Dynamic Method).

10. Verification of truth table using AND, OR logic gates.

Course Learning Outcomes (CLOs):

CLO1: Learn the practical knowledge of theoretical studies.

CLO2: Develop skills to impart practical knowledge in real-time solutions by teamwork.

CLO3: Able to understand measurement technologies, usage of lab instruments, and real-time applications of Physics in engineering studies.

References:

Learning Materials:

Textbooks:

1. David M. Loyd, Physics Laboratory Manual, Third Edition

2. Physics 103A Laboratory Manual 10th Edition

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Physics Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

A Physics lab is very important to learn the relevance between the theory and real solutions. This course will teach the students to implement and prove different types of Physics laws and rules and they will learn about how to be patient and careful during observation and calculation. Students will acquire knowledge about the application of Physics to get an elaborate idea of the rules and equations.

Experiments:

1. Verification of Ohm’s Law.

2. Calculating Young’s Modulus of a wire using the Vernier scale.

3. Determination of the value of the Acceleration due to Gravity(g) with the help of a compound(bar) pendulum.

4. Determination of the gravitational acceleration (g) by using a simple pendulum and verification of the formula.

5. Determination of the spring constant and effective mass of a given spiral spring.

6. Investigate the characteristics of series DC circuits and verify Kirchhoff's Voltage Law (KVL).

7. Determination of the radius of the curvature of a plano-convex lens by Newton’s rings method.

8. Determination of Young’s modulus of the given material bar by non-uniform bending using the pin and microscope method.

9. Determination of the moment of inertia of a given disc using a Torsion pendulum by the method of oscillations (Dynamic Method).

10. Verification of truth table using AND, OR logic gates.

Course Learning Outcomes (CLOs):

CLO1: Learn the practical knowledge of theoretical studies.

CLO2: Develop skills to impart practical knowledge in real-time solutions by teamwork.

CLO3: Able to understand measurement technologies, usage of lab instruments, and real-time applications of Physics in engineering studies.

References:

Learning Materials:

Textbooks:

1. David M. Loyd, Physics Laboratory Manual, Third Edition

2. Physics 103A Laboratory Manual 10th Edition

Other Learning Materials: Journals, Web Materials, etc.

Course Code: HRM 1103 - 0413

Course Title: Organizational Behavior

Course Type: Theory

Prerequisite: None

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

This is an introductory course in financial management that is designed to get an overview of the major decisions made by the finance department of an organization. This course is designed to provide the foundation on topics that include major finance functions of the business, understanding financial information, relevant tools to analyze, interpret, and evaluate financial statements, understanding time value-of-money, its relevance to evaluating investment decisions, the concept of risk and return related to financial decisions, introduction to financial institutions, investments, and corporate finance.

Course Contents:

1. Introduction to Organizational Behavior: Concept of Organizational Behavior -Basic Management Functions-Managerial Roles-Management Skills, Contributing Discipline to OB Field-Challenges and Opportunity for OB, Basic OB Model.

2. Foundations of individual behavior: Intellectual ability, physical ability, Biographical Characteristics, Differences among Learning, Training, & Education. of setting stretch objectives- the need for short-term and long-term objectives- setting financial objectives- setting strategic objectives- crafting a strategy- executing the strategy- evaluating performance and initiating corrective adjustments.

3. Values, Attitudes & Job Satisfaction: Values-Types of Values-Values, Loyalty, and Ethical Behavior-Hofstede’s Framework for Assessing Cultures, Attitudes-Types of Attitudes-The Theory of Cognitive Dissonance-Self-Perception Theory, Job Satisfaction-The Effect of Job Satisfaction on Employee Performance-How Employees Can Express Dissatisfaction.

4. Personality & Emotions: Personality-Personality Traits-The Myers-Briggs Type Indicator, Major Personality Attributes Influencing OB. Emotions- Meaning of Emotions & Mood, Differences between Emotion & Mood, Why Emotions Were Ignored in OB-Emotion Dimensions-OB Applications of Understanding Emotions, the structure of moods, positive affect, negative affect, positivity offset.

Perception and Individual Decision Making: Perception, factors that influence employee perception, Common Shortcuts in Judging Others, Influences on Decision Making. Individual Differences and Organizational Constraints.

5. Communication: Functions of Communication- The Communication Process Model- Direction of Communication- Interpersonal Communication, Three Common Formal Small-Group Networks- Grapevine- Computer-Aided Communication- Barriers to Effective Communication.

6. Motivation: Motivation, Motivation process, ways to motivation, performance & motivation, Working efficiency and motivation, Maslow’s Need Hierarchy Theory. X & Y Theory of Motivation, Two Factors Theory, Expectancy Theory and its criticism.

7. Leadership: Definition-Types-Approaches/Theories of Leadership, Approaches/Theories of Leadership.

8. Organizational Culture: Organizational Culture-Importance-Characteristics, Keeping Culture Alive- Stages in the Socialization Process.

9. Power & Politics: A Definition of Power-Leadership and Power-Bases of Power-Power Tactics, Power in Groups-Power in Action-Employee Responses to Organizational Politics-Impression Management.

10. Conflict & Negotiation: Conflict-Types of Conflict-Components of Conflict, Resolution techniques of Conflict, Negotiation Definition, Process of Negotiation.

11. Understanding Work Team: Team Versus Groups- Types of Teams- Creating Effective Teams, Contemporary Issues in Managing Teams- Team and Workforce Diversity.

12. Defining & Classifying Groups: Group, Formal group, informal group, why people join group, Five Stages of Group Development Model. Critique of the Five-Stage Model, Punctuated-Equilibrium Model, Group Properties.

Course Learning Outcomes:

CLO1: Describe basic principles, concepts, and methods of financial management and explain the objectives and role of the financial manager in a corporation.

CLO2: Analyze financial statements to make decisions about the stock and bonds of the company using information technology.

CLO3: Evaluate investment strategies and decisions using the time value of money principles and calculate the cost of capital for financial decision-making purposes.

CLO4: Communicate with various audiences to raise the awareness of decision-makers.

CLO5: Cooperate with the team to disseminate information and propose solutions to maximize shareholders' wealth and the company’s profit.

References:

Textbooks:

1. Stephen P Robbins, Timothy A. Judge, Seema Sanghi. Organizational Behavior, 13th edition, Prentice-Hall.

2. Keith Davis, John W Newstorm. Manpower Planning and Organization Design. Latest Edition

3. Md.Faruk Hosen, Md. Shelim Miah, Md. Nur-E-Alam Siddique. Organizational Behavior. Latest Edition.

4. Fred Luthans, Organizational Behavior, 12th edition, McGraw Hill.

Other Learning Materials: Journals, Website Materials, YouTube Videos, etc.

Course Title: Organizational Behavior

Course Type: Theory

Prerequisite: None

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

This is an introductory course in financial management that is designed to get an overview of the major decisions made by the finance department of an organization. This course is designed to provide the foundation on topics that include major finance functions of the business, understanding financial information, relevant tools to analyze, interpret, and evaluate financial statements, understanding time value-of-money, its relevance to evaluating investment decisions, the concept of risk and return related to financial decisions, introduction to financial institutions, investments, and corporate finance.

Course Contents:

1. Introduction to Organizational Behavior: Concept of Organizational Behavior -Basic Management Functions-Managerial Roles-Management Skills, Contributing Discipline to OB Field-Challenges and Opportunity for OB, Basic OB Model.

2. Foundations of individual behavior: Intellectual ability, physical ability, Biographical Characteristics, Differences among Learning, Training, & Education. of setting stretch objectives- the need for short-term and long-term objectives- setting financial objectives- setting strategic objectives- crafting a strategy- executing the strategy- evaluating performance and initiating corrective adjustments.

3. Values, Attitudes & Job Satisfaction: Values-Types of Values-Values, Loyalty, and Ethical Behavior-Hofstede’s Framework for Assessing Cultures, Attitudes-Types of Attitudes-The Theory of Cognitive Dissonance-Self-Perception Theory, Job Satisfaction-The Effect of Job Satisfaction on Employee Performance-How Employees Can Express Dissatisfaction.

4. Personality & Emotions: Personality-Personality Traits-The Myers-Briggs Type Indicator, Major Personality Attributes Influencing OB. Emotions- Meaning of Emotions & Mood, Differences between Emotion & Mood, Why Emotions Were Ignored in OB-Emotion Dimensions-OB Applications of Understanding Emotions, the structure of moods, positive affect, negative affect, positivity offset.

Perception and Individual Decision Making: Perception, factors that influence employee perception, Common Shortcuts in Judging Others, Influences on Decision Making. Individual Differences and Organizational Constraints.

5. Communication: Functions of Communication- The Communication Process Model- Direction of Communication- Interpersonal Communication, Three Common Formal Small-Group Networks- Grapevine- Computer-Aided Communication- Barriers to Effective Communication.

6. Motivation: Motivation, Motivation process, ways to motivation, performance & motivation, Working efficiency and motivation, Maslow’s Need Hierarchy Theory. X & Y Theory of Motivation, Two Factors Theory, Expectancy Theory and its criticism.

7. Leadership: Definition-Types-Approaches/Theories of Leadership, Approaches/Theories of Leadership.

8. Organizational Culture: Organizational Culture-Importance-Characteristics, Keeping Culture Alive- Stages in the Socialization Process.

9. Power & Politics: A Definition of Power-Leadership and Power-Bases of Power-Power Tactics, Power in Groups-Power in Action-Employee Responses to Organizational Politics-Impression Management.

10. Conflict & Negotiation: Conflict-Types of Conflict-Components of Conflict, Resolution techniques of Conflict, Negotiation Definition, Process of Negotiation.

11. Understanding Work Team: Team Versus Groups- Types of Teams- Creating Effective Teams, Contemporary Issues in Managing Teams- Team and Workforce Diversity.

12. Defining & Classifying Groups: Group, Formal group, informal group, why people join group, Five Stages of Group Development Model. Critique of the Five-Stage Model, Punctuated-Equilibrium Model, Group Properties.

Course Learning Outcomes:

CLO1: Describe basic principles, concepts, and methods of financial management and explain the objectives and role of the financial manager in a corporation.

CLO2: Analyze financial statements to make decisions about the stock and bonds of the company using information technology.

CLO3: Evaluate investment strategies and decisions using the time value of money principles and calculate the cost of capital for financial decision-making purposes.

CLO4: Communicate with various audiences to raise the awareness of decision-makers.

CLO5: Cooperate with the team to disseminate information and propose solutions to maximize shareholders' wealth and the company’s profit.

References:

Textbooks:

1. Stephen P Robbins, Timothy A. Judge, Seema Sanghi. Organizational Behavior, 13th edition, Prentice-Hall.

2. Keith Davis, John W Newstorm. Manpower Planning and Organization Design. Latest Edition

3. Md.Faruk Hosen, Md. Shelim Miah, Md. Nur-E-Alam Siddique. Organizational Behavior. Latest Edition.

4. Fred Luthans, Organizational Behavior, 12th edition, McGraw Hill.

Other Learning Materials: Journals, Website Materials, YouTube Videos, etc.

Course Code: HUM 1113-0222

Course Title: Bangladesh Studies

Course Type: Theory

Prerequisite: N/A

Credits: 2

Contact Hours: 28

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course has been designed for undergraduate students to help them learn the rich history of Bangladesh, to understand present Bangladesh in the light of history, and to provide them with basic knowledge of the current politics and economy of the country. This course will deepen students' understanding of the complex interconnection of historical events which lead to the formation of Bangladesh, the current trend in political and economic development thereby improving critical thinking along with their written and oral communication skills, quantitative skills, and technical literacy. It will also enhance their understanding of current phenomena in the light of history which will make them responsible global citizens. The course intends to equip students with factual knowledge and analytical skills that will enable them to learn and critically appreciate the history, politics, and economy of Bangladesh. It will trace the historical roots of Bangladesh as an independent state focusing on the social, economic, and political developments that have taken place since its independence. It will also identify the major socio-economic, political, environmental, and developmental issues that have arisen during this period, before assessing the progress over time.

Course Contents:

➢ Anthropological Background of Bengalis

➢ Establishment of Muslim Rule in Bengal

➢ Liberation War

➢ Government of Bangladesh

➢ Economy of Bangladesh

➢ Agriculture of Bangladesh

➢ Industry of Bangladesh

➢ Economic Planning

Course Learning Outcomes (CLOs):

CLO1: Identify specific stages of Bangladesh’s political history, through the ancient, medieval, colonial, and post-colonial periods and critically analyze the plurality of cultural identities of Bangladesh.

CLO2: Analyze how different constitutional bodies and socio-political institutions operate and how their behavior impacts on political governance.

CLO3: Explain the economy and patterns of economic changes through qualitative and quantitative analysis. This will increase their awareness of global issues of development processes and the nature of environmental challenges including ways to address them effectively.

CLO4: Appreciate the role of NGOs and civil society in developing new models and pathways to resolve the range of development challenges that the country is currently facing.

References:

Textbooks:

Bangladesh Studies, MD Hasibur Rahman

Reference Books:

1. Constitutional Law, Barrister Halim

2. Secondary Economics, NCTB

3. Bangladesh Studies, Md. Shamsul Kabir Khan

4. Bangladesh Economics (Bangla Version), Akmol Mahmud

5. The Economics of Development and Planning, ML Jhingan

Learning Materials: Journals, Websites.

Course Title: Bangladesh Studies

Course Type: Theory

Prerequisite: N/A

Credits: 2

Contact Hours: 28

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course has been designed for undergraduate students to help them learn the rich history of Bangladesh, to understand present Bangladesh in the light of history, and to provide them with basic knowledge of the current politics and economy of the country. This course will deepen students' understanding of the complex interconnection of historical events which lead to the formation of Bangladesh, the current trend in political and economic development thereby improving critical thinking along with their written and oral communication skills, quantitative skills, and technical literacy. It will also enhance their understanding of current phenomena in the light of history which will make them responsible global citizens. The course intends to equip students with factual knowledge and analytical skills that will enable them to learn and critically appreciate the history, politics, and economy of Bangladesh. It will trace the historical roots of Bangladesh as an independent state focusing on the social, economic, and political developments that have taken place since its independence. It will also identify the major socio-economic, political, environmental, and developmental issues that have arisen during this period, before assessing the progress over time.

Course Contents:

➢ Anthropological Background of Bengalis

➢ Establishment of Muslim Rule in Bengal

➢ Liberation War

➢ Government of Bangladesh

➢ Economy of Bangladesh

➢ Agriculture of Bangladesh

➢ Industry of Bangladesh

➢ Economic Planning

Course Learning Outcomes (CLOs):

CLO1: Identify specific stages of Bangladesh’s political history, through the ancient, medieval, colonial, and post-colonial periods and critically analyze the plurality of cultural identities of Bangladesh.

CLO2: Analyze how different constitutional bodies and socio-political institutions operate and how their behavior impacts on political governance.

CLO3: Explain the economy and patterns of economic changes through qualitative and quantitative analysis. This will increase their awareness of global issues of development processes and the nature of environmental challenges including ways to address them effectively.

CLO4: Appreciate the role of NGOs and civil society in developing new models and pathways to resolve the range of development challenges that the country is currently facing.

References:

Textbooks:

Bangladesh Studies, MD Hasibur Rahman

Reference Books:

1. Constitutional Law, Barrister Halim

2. Secondary Economics, NCTB

3. Bangladesh Studies, Md. Shamsul Kabir Khan

4. Bangladesh Economics (Bangla Version), Akmol Mahmud

5. The Economics of Development and Planning, ML Jhingan

Learning Materials: Journals, Websites.

Course Code: ENG-1213-0231

Course Title: Communicative English

Course Type: Theory

Prerequisite: N/A

Credits: 2

Contact Hours: 28

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

The Communicative English course is essential for students to enhance their fundamental English language skills and analytical power in order to combine them into their core disciplines and, to a greater extent, to use them in real-life circumstances. The course focuses on the tactics, techniques, and strategies required to explain various circumstances and examine various ideas in order to improve students' comprehension and learning through reflective practice.

Course Contents:

➢ Sentence level errors: most common mistakes- correcting sentences, fragments, run-ons

➢ Grammar: Uses of Tenses, Verbs, Subject-Verb Agreement

➢ Grammar: Modals, Gerund, Participles, Conditionals, Preposition

➢ Grammar: Voices, Direct and Indirect Speeches

➢ Reading: Purposes of reading; reading strategies: Skimming, Scanning, Inferencing

➢ Reading: practice

➢ Mechanics of writing: Uses of a full stop, comma, colon, semicolon, apostrophe, capital letter, a hyphen, quotation marks

➢ Writing Stages: Brainstorming, Pre-Writing, Drafting, Proofreading, and Editing

➢ Paragraph: Topic Sentence, Parts of a Paragraph, Types of Paragraphs

➢ Listening: Listening for key ideas, and specific details. Listening and note-taking. Listening to conversations, lectures, news items, and songs

➢ Speaking: Formal/Informal conversations, Role plays, Interviews, Short presentations, Storytelling, and Debating

➢ Formal letter/email writing

Course Learning Outcomes (CLOs):

After completing this course, students would be able to:

CLO1: Identify and adopt different techniques for reading academic and non-academic textbooks.

CLO2: Adapt different techniques of listening to academic and non-academic conversations.

CLO3: Develop confidence in initiating a conversation in the target language.

CLO4: Develop a willingness to establish social communication.

CLO5: Start generating ideas on an academic topic by thinking critically and ethically.

References:

Textbooks:

1. Kumar, S., & Lata, P. (2011). Communication skills (Vol. 4). New Delhi: Oxford University Press.

2. Konar, N. (2021). Communication skills for professionals. PHI Learning Pvt. Ltd.

Other Learning Materials: Journals, Website Materials, YouTube Videos, etc.

Course Title: Communicative English

Course Type: Theory

Prerequisite: N/A

Credits: 2

Contact Hours: 28

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

The Communicative English course is essential for students to enhance their fundamental English language skills and analytical power in order to combine them into their core disciplines and, to a greater extent, to use them in real-life circumstances. The course focuses on the tactics, techniques, and strategies required to explain various circumstances and examine various ideas in order to improve students' comprehension and learning through reflective practice.

Course Contents:

➢ Sentence level errors: most common mistakes- correcting sentences, fragments, run-ons

➢ Grammar: Uses of Tenses, Verbs, Subject-Verb Agreement

➢ Grammar: Modals, Gerund, Participles, Conditionals, Preposition

➢ Grammar: Voices, Direct and Indirect Speeches

➢ Reading: Purposes of reading; reading strategies: Skimming, Scanning, Inferencing

➢ Reading: practice

➢ Mechanics of writing: Uses of a full stop, comma, colon, semicolon, apostrophe, capital letter, a hyphen, quotation marks

➢ Writing Stages: Brainstorming, Pre-Writing, Drafting, Proofreading, and Editing

➢ Paragraph: Topic Sentence, Parts of a Paragraph, Types of Paragraphs

➢ Listening: Listening for key ideas, and specific details. Listening and note-taking. Listening to conversations, lectures, news items, and songs

➢ Speaking: Formal/Informal conversations, Role plays, Interviews, Short presentations, Storytelling, and Debating

➢ Formal letter/email writing

Course Learning Outcomes (CLOs):

After completing this course, students would be able to:

CLO1: Identify and adopt different techniques for reading academic and non-academic textbooks.

CLO2: Adapt different techniques of listening to academic and non-academic conversations.

CLO3: Develop confidence in initiating a conversation in the target language.

CLO4: Develop a willingness to establish social communication.

CLO5: Start generating ideas on an academic topic by thinking critically and ethically.

References:

Textbooks:

1. Kumar, S., & Lata, P. (2011). Communication skills (Vol. 4). New Delhi: Oxford University Press.

2. Konar, N. (2021). Communication skills for professionals. PHI Learning Pvt. Ltd.

Other Learning Materials: Journals, Website Materials, YouTube Videos, etc.

Course Code: MATH-1213-0541

Course Title: Mathematics II

Course Type: Theory

Prerequisite: MATH 1111-0541

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

Linear algebra is essential to develop algorithms, software and scientific computations. Complex variable and Vector analysis are powerful tools for doing mathematical analysis in engineering fields. This course is designed to provide theoretical knowledge regarding matrices, vector space, eigenvalues and eigenvectors, complex differentiations and integrations, vector differentiations and integrations, and its related theories.

Course Contents:

1. Linear Algebra: Solution of the system of linear equations, Determinant, Matrix, Rank, and nullity of the matrix, Vector space, Direct sum, Linear dependence and independence, Basis, and dimension. Linear transformation, Eigenvalues and EigenVectors, Norms and inner products, Gram-Schmidt orthogonalization process, Hermitian, Unitary, Orthogonal and Normal operators, Matrix representation.

2. Complex differentiation: Functions of a complex variable, Limits, and continuity of functions of a complex variable; Complex differentiation and Cauchy- Riemann Equations; Mapping by elementary functions;

3. Complex integration: Line integral of a complex function; Cauchy’s Integral Theorem; Cauchy’s Integral Formula; Liouville’s Theorem; Taylor’s Theorem and Laurent’s theorem; Singular points; Residue; Cauchy’s Residue Theorem; Contour integration.

4. Vector differentiation: Differentiation of vectors with elementary applications, Gradient, divergence, and curl of point functions.

5. Vector integration: Line, Surface, and Volume integrals; Green’s theorem; Gauss’s theorem; Stoke’s theorem.

Course Learning Outcomes (CLOs):

CLO1: Students will be able to understand systems of linear equations, matrices, functions of complex variables, vector calculus, and related theories.

CLO2: Analyze properties of systems of linear equations, matrices, eigenvalues and eigenvectors, functions of complex variables, vector spaces, and dimensions.

CLO3: Determine the solution of a system of linear equations, matrices, eigenvalues and eigenvectors, complex functions, singularities, differentiation, and integration.

CLO4: Apply acquired knowledge in solving problems arising in engineering applications.

CLO5: Develop algorithms and software relating to engineering applications.

References:

Learning Materials:

Textbooks:

1. Lipschutz, S. 2005. Linear Algebra,3rded, McGraw-Hill Co., New Delhi.

2. Howard Anton. 2005. Elementary Linear Algebra, 1sted, Wiley & Sons, USA.

3. Murray R. Spiegel, 1999. Complex Variables, 2nd ed, McGraw-Hill, NY

4. Ahlfors, L.V. 1966. Complex Analysis, 2nd ed, McGraw-Hill, NY.

5. Spiegel, M.R. 2004. Vector Analysis,4thed, McGraw-Hill Co., New Delhi.

6. Gupta & Malik. 2000. Vector Analysis, 8th ed, Kedar Nath Ram Nath, Meerut.

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Mathematics II

Course Type: Theory

Prerequisite: MATH 1111-0541

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

Linear algebra is essential to develop algorithms, software and scientific computations. Complex variable and Vector analysis are powerful tools for doing mathematical analysis in engineering fields. This course is designed to provide theoretical knowledge regarding matrices, vector space, eigenvalues and eigenvectors, complex differentiations and integrations, vector differentiations and integrations, and its related theories.

Course Contents:

1. Linear Algebra: Solution of the system of linear equations, Determinant, Matrix, Rank, and nullity of the matrix, Vector space, Direct sum, Linear dependence and independence, Basis, and dimension. Linear transformation, Eigenvalues and EigenVectors, Norms and inner products, Gram-Schmidt orthogonalization process, Hermitian, Unitary, Orthogonal and Normal operators, Matrix representation.

2. Complex differentiation: Functions of a complex variable, Limits, and continuity of functions of a complex variable; Complex differentiation and Cauchy- Riemann Equations; Mapping by elementary functions;

3. Complex integration: Line integral of a complex function; Cauchy’s Integral Theorem; Cauchy’s Integral Formula; Liouville’s Theorem; Taylor’s Theorem and Laurent’s theorem; Singular points; Residue; Cauchy’s Residue Theorem; Contour integration.

4. Vector differentiation: Differentiation of vectors with elementary applications, Gradient, divergence, and curl of point functions.

5. Vector integration: Line, Surface, and Volume integrals; Green’s theorem; Gauss’s theorem; Stoke’s theorem.

Course Learning Outcomes (CLOs):

CLO1: Students will be able to understand systems of linear equations, matrices, functions of complex variables, vector calculus, and related theories.

CLO2: Analyze properties of systems of linear equations, matrices, eigenvalues and eigenvectors, functions of complex variables, vector spaces, and dimensions.

CLO3: Determine the solution of a system of linear equations, matrices, eigenvalues and eigenvectors, complex functions, singularities, differentiation, and integration.

CLO4: Apply acquired knowledge in solving problems arising in engineering applications.

CLO5: Develop algorithms and software relating to engineering applications.

References:

Learning Materials:

Textbooks:

1. Lipschutz, S. 2005. Linear Algebra,3rded, McGraw-Hill Co., New Delhi.

2. Howard Anton. 2005. Elementary Linear Algebra, 1sted, Wiley & Sons, USA.

3. Murray R. Spiegel, 1999. Complex Variables, 2nd ed, McGraw-Hill, NY

4. Ahlfors, L.V. 1966. Complex Analysis, 2nd ed, McGraw-Hill, NY.

5. Spiegel, M.R. 2004. Vector Analysis,4thed, McGraw-Hill Co., New Delhi.

6. Gupta & Malik. 2000. Vector Analysis, 8th ed, Kedar Nath Ram Nath, Meerut.

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 2141-0613

Course Title: Object-Oriented Programming Language

Course Type: Theory

Prerequisite: CSE 1213-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

Object Oriented Programming (OOP) is a programming architecture that relies on Class, Object, Inheritance, Polymorphism, Encapsulation, and Abstraction. Students will be able to learn OOP in order to Graphical User Interface (GUI) based desktop/ web application development.

Course Contents:

1. Fundamental Programming Structures in Java: Main() method, Primitive Data Types, Variables, Constants, Assignments, Initializations, Operators, Strings, Control Flow, Code Examples, and Exercises.

2. Classes and Objects in Java: Classes & Objects, OOP Principles, Instance Variables, Class Variables, Constructors, Instance Methods, Class Methods, Method Overloading, This Keyword, Passing and Returning Objects, Garbage Collection in Java, Code Examples & Exercises.

3. Object Design and Programming with Java: Abstraction, Inheritance, Polymorphism, Method Overriding, Associations, Delegations, Code Examples, and Exercises.

4. Java Interfaces: Purpose of interfaces, Usage, Interface Declaration, Implementing and Interface, Interface Inheritance, Code Examples, and Exercises.

5. Java Exception Handling: Exceptions, Standard Exception Handling, Exception Class Hierarchy, checked vs Unchecked Exception, Catching an Exception, Exception Handling, Writing Exception, Code Examples, and Exercises.

6. Collections of API: Arrays, Java Collections Framework, Collections Interfaces, Concrete Collections, Code Examples, and Exercises

7. Java Input/Output API: Streams and Files, I/O Streams, File Streams, Readers and Writers, Code Examples, and Exercises.

8. Java Threading & GUI: Java Multithreading, Menus, Toolbars, Dialogs, Containers, Layout Management.

Course Learning Outcomes (CLOs):

CLO1: Students will be able to understand the basic paradigm of OOP and the syntax of Java/JSP/ Python/ C#.

CLO2: Able to gain knowledge on all components of OOP and design the solutions using a programming language.

CLO3: Competent to identify, analyze and solve complex problems.

CLO4: Able to select advanced tools and apply OOP to solve advanced real-world problems.

References:

Learning Materials:

Textbooks:

1. Paul Deitel, Harvey Deitel, Java How to Program, Ninth Edition.

2. Kathy Sierra, Bert Bates, Sun Certified Programmer for Java 6 Study Guide

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Object-Oriented Programming Language

Course Type: Theory

Prerequisite: CSE 1213-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

Object Oriented Programming (OOP) is a programming architecture that relies on Class, Object, Inheritance, Polymorphism, Encapsulation, and Abstraction. Students will be able to learn OOP in order to Graphical User Interface (GUI) based desktop/ web application development.

Course Contents:

1. Fundamental Programming Structures in Java: Main() method, Primitive Data Types, Variables, Constants, Assignments, Initializations, Operators, Strings, Control Flow, Code Examples, and Exercises.

2. Classes and Objects in Java: Classes & Objects, OOP Principles, Instance Variables, Class Variables, Constructors, Instance Methods, Class Methods, Method Overloading, This Keyword, Passing and Returning Objects, Garbage Collection in Java, Code Examples & Exercises.

3. Object Design and Programming with Java: Abstraction, Inheritance, Polymorphism, Method Overriding, Associations, Delegations, Code Examples, and Exercises.

4. Java Interfaces: Purpose of interfaces, Usage, Interface Declaration, Implementing and Interface, Interface Inheritance, Code Examples, and Exercises.

5. Java Exception Handling: Exceptions, Standard Exception Handling, Exception Class Hierarchy, checked vs Unchecked Exception, Catching an Exception, Exception Handling, Writing Exception, Code Examples, and Exercises.

6. Collections of API: Arrays, Java Collections Framework, Collections Interfaces, Concrete Collections, Code Examples, and Exercises

7. Java Input/Output API: Streams and Files, I/O Streams, File Streams, Readers and Writers, Code Examples, and Exercises.

8. Java Threading & GUI: Java Multithreading, Menus, Toolbars, Dialogs, Containers, Layout Management.

Course Learning Outcomes (CLOs):

CLO1: Students will be able to understand the basic paradigm of OOP and the syntax of Java/JSP/ Python/ C#.

CLO2: Able to gain knowledge on all components of OOP and design the solutions using a programming language.

CLO3: Competent to identify, analyze and solve complex problems.

CLO4: Able to select advanced tools and apply OOP to solve advanced real-world problems.

References:

Learning Materials:

Textbooks:

1. Paul Deitel, Harvey Deitel, Java How to Program, Ninth Edition.

2. Kathy Sierra, Bert Bates, Sun Certified Programmer for Java 6 Study Guide

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 2142-0613

Course Title: Object-Oriented Programming Language Lab

Course Type: Lab

Prerequisite: CSE 1213-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

This course aims to increase coding skills based on Object Oriented Programming (OOP) using Java/JSP/Python/C#.

Lab Tasks:

➢ Set up Java environment, Introduction to Java, and visualization of Main() Method.

➢ Exploring the data types of Java

➢ Create Classes and Objects, Instances and Methods

➢ Create Constructor, learn to use Return

➢ Introduction to OOP Principles

➢ Implementation of Inheritance and Polymorphism

➢ Implementation of Abstraction, Encapsulation

➢ Implementation of Interfaces

➢ Group project: Effective idea submission and presentation

➢ Working with Exception Handling and learning Exception Class Hierarchy

➢ Create Try & Catch Blocks, Custom Exception Writing

➢ Working with Java Collection Frameworks (List, Map, Set, Collections), Iterating Through Collections

➢ Implementation of Java Input/Output API, File Streams, Readers, and Writers

➢ Java GUI Implementation

➢ Review of Project Implementation

➢ Review of GUI and Layout of the project

➢ Final Project Submission and Presentation

Course Learning Outcomes (CLOs):

CLO1: Students will be able to gain programming knowledge and practice through various IDE of Java/JSP/Python/C#.

CLO2: Able to identify problems, design the structure, analyze, and coding to create applications by system software.

CLO3: Able to research and implement OOP to solve various engineering problems during the development process in dispersed situations.

References:

Learning Materials:

Textbooks:

1. Paul Deitel, Harvey Deitel, Java How to Program, Ninth Edition

2. Kathy Sierra, Bert Bates, Sun Certified Programmer for Java 6 Study Guide

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Object-Oriented Programming Language Lab

Course Type: Lab

Prerequisite: CSE 1213-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

This course aims to increase coding skills based on Object Oriented Programming (OOP) using Java/JSP/Python/C#.

Lab Tasks:

➢ Set up Java environment, Introduction to Java, and visualization of Main() Method.

➢ Exploring the data types of Java

➢ Create Classes and Objects, Instances and Methods

➢ Create Constructor, learn to use Return

➢ Introduction to OOP Principles

➢ Implementation of Inheritance and Polymorphism

➢ Implementation of Abstraction, Encapsulation

➢ Implementation of Interfaces

➢ Group project: Effective idea submission and presentation

➢ Working with Exception Handling and learning Exception Class Hierarchy

➢ Create Try & Catch Blocks, Custom Exception Writing

➢ Working with Java Collection Frameworks (List, Map, Set, Collections), Iterating Through Collections

➢ Implementation of Java Input/Output API, File Streams, Readers, and Writers

➢ Java GUI Implementation

➢ Review of Project Implementation

➢ Review of GUI and Layout of the project

➢ Final Project Submission and Presentation

Course Learning Outcomes (CLOs):

CLO1: Students will be able to gain programming knowledge and practice through various IDE of Java/JSP/Python/C#.

CLO2: Able to identify problems, design the structure, analyze, and coding to create applications by system software.

CLO3: Able to research and implement OOP to solve various engineering problems during the development process in dispersed situations.

References:

Learning Materials:

Textbooks:

1. Paul Deitel, Harvey Deitel, Java How to Program, Ninth Edition

2. Kathy Sierra, Bert Bates, Sun Certified Programmer for Java 6 Study Guide

Other Learning Materials: Journals, Web Materials, etc.

Course Code: EEE 1211-0714

Course Title: Electrical Circuit Analysis

Course Type: Theory

Prerequisite: PHY-1111-0533

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

Electrical circuit analysis covers the fundamental methods and principles required for the design and analysis of electrical systems. This course is intended to provide a basic knowledge of electrical circuits and circuit analysis, which includes both DC and AC circuits, and an analysis of those circuits.

Course Contents:

1. Circuit variables: voltage, current, power and energy, Voltage and current independent and

dependent sources, Circuit elements resistance, inductance, and capacitance. Modeling of practical circuits, Ohm’s law and Kirchhoff’s laws, Solution of simple circuits with both dependent and independent sources, Series-parallel resistance circuits and their equivalents, Voltage and current divider circuits, Delta-Wye equivalent circuits.

2. Techniques of general DC circuit analysis: Node-voltage method, Mesh-current method, Source transformations. Thevenin and Norton equivalents, Maximum power transfer. Superposition technique. Properties of Inductances and capacitances. Series-parallel combinations of inductances and capacitances.

3. Sinusoidal functions: Instantaneous current, voltage, power, effective current and voltage,

average power, phasors and complex quantities, impedance, real and reactive power, power factor; Analysis of single-phase AC circuits: Series and parallel RL, RC and RLC circuits, nodal and mesh analysis, application of network theorems in AC circuits.

Course Learning Outcomes (CLOs):

CLO1: Learn about the basic concepts of voltage, current, power, energy, sources, resistance, energy storage elements, and circuit configurations.

CLO2: Apply different analysis techniques to solve booth DC resistive circuits as well as AC circuits.

CLO3: Analyze natural and step responses of RL, RC, and RLC circuits.

CLO4: Build basic electrical circuits and operate fundamental circuit lab equipment.

CLO5: Use PSpice/Proteus tool to simulate both DC and AC circuits.

References:

Learning Materials:

Textbooks:

1. Introductory Circuit Analysis - R.L. Boylestad; Prentice Hall of India Private Ltd.

2. Fundamental of Electric Circuit by Alexander and Sadiku (Fifth Edition)

3. Introduction to Electric Circuits by R. C. Dorf& J. A. Svoboda (4th Edition)

Other Learning Materials: Journals, websites, YouTube videos.

Course Title: Electrical Circuit Analysis

Course Type: Theory

Prerequisite: PHY-1111-0533

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

Electrical circuit analysis covers the fundamental methods and principles required for the design and analysis of electrical systems. This course is intended to provide a basic knowledge of electrical circuits and circuit analysis, which includes both DC and AC circuits, and an analysis of those circuits.

Course Contents:

1. Circuit variables: voltage, current, power and energy, Voltage and current independent and

dependent sources, Circuit elements resistance, inductance, and capacitance. Modeling of practical circuits, Ohm’s law and Kirchhoff’s laws, Solution of simple circuits with both dependent and independent sources, Series-parallel resistance circuits and their equivalents, Voltage and current divider circuits, Delta-Wye equivalent circuits.

2. Techniques of general DC circuit analysis: Node-voltage method, Mesh-current method, Source transformations. Thevenin and Norton equivalents, Maximum power transfer. Superposition technique. Properties of Inductances and capacitances. Series-parallel combinations of inductances and capacitances.

3. Sinusoidal functions: Instantaneous current, voltage, power, effective current and voltage,

average power, phasors and complex quantities, impedance, real and reactive power, power factor; Analysis of single-phase AC circuits: Series and parallel RL, RC and RLC circuits, nodal and mesh analysis, application of network theorems in AC circuits.

Course Learning Outcomes (CLOs):

CLO1: Learn about the basic concepts of voltage, current, power, energy, sources, resistance, energy storage elements, and circuit configurations.

CLO2: Apply different analysis techniques to solve booth DC resistive circuits as well as AC circuits.

CLO3: Analyze natural and step responses of RL, RC, and RLC circuits.

CLO4: Build basic electrical circuits and operate fundamental circuit lab equipment.

CLO5: Use PSpice/Proteus tool to simulate both DC and AC circuits.

References:

Learning Materials:

Textbooks:

1. Introductory Circuit Analysis - R.L. Boylestad; Prentice Hall of India Private Ltd.

2. Fundamental of Electric Circuit by Alexander and Sadiku (Fifth Edition)

3. Introduction to Electric Circuits by R. C. Dorf& J. A. Svoboda (4th Edition)

Other Learning Materials: Journals, websites, YouTube videos.

Course Code: EEE 1212-0714

Course Title: Electrical Circuit Analysis Lab

Course Type: Lab

Prerequisite: PHY-1111-0533

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

Electrical circuit analysis Lab is the basic course that is intended to teach the basics of electrical circuits to the undergraduates of computer science and engineering departments. The main aim of this course is to acquire and get familiar with the fundamentals of electrical circuit components, as well as the practical analysis of both DC and AC circuits.

Course Contents:

Exp1: Verification of Ohm’s Law, Kirchhoff’s current law, and voltage law using hardware and digital simulation.

Exp2: Verification of mesh analysis using hardware and digital simulation.

Exp3: Verification of nodal analysis using hardware and digital simulation.

Exp4: Determination of average value, rms value, form factor, and peak factor of a sinusoidal wave, and square wave using hardware and digital simulation.

Exp5: Measurement of power and power factor correction.

Exp6: Verification of maximum power transfer theorem using hardware and digital simulation.

Exp7: Verification of Thevenin’s theorem using hardware and digital simulation.

Exp8: Verification of Norton’s theorem using hardware and digital simulation.

Exp9: Study of Resonance Behavior of a parallel RLC circuit with a variable capacitor.

Exp10: Study of a 3-phase system with a balanced load.

Exp11: Verification of self-inductance and mutual inductance by using hardware.

Course Learning Outcomes (CLOs):

CLO1: Familiar with DC and AC circuit analysis techniques.

CLO2: Analyze complicated circuits using different network theorems.

CLO3: Acquire skills in using PSpice/Proteus software for electrical circuit studies.

CLO4: Determine the self and mutual inductance of coupled coils.

CLO5: Demonstrate proficiency in identifying circuit components on a schematic drawing and in a lab setting.

References:

Learning Materials:

Textbooks:

1) Fundamentals of Electric circuit by Charles k. Alexander.

2) DC Electrical Circuit Analysis: A Practical Approach by James M Flore.

3) PSpice and Proteus software (Updated version).

Other Learning Materials: Journals, websites, YouTube videos.

Course Title: Electrical Circuit Analysis Lab

Course Type: Lab

Prerequisite: PHY-1111-0533

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

Electrical circuit analysis Lab is the basic course that is intended to teach the basics of electrical circuits to the undergraduates of computer science and engineering departments. The main aim of this course is to acquire and get familiar with the fundamentals of electrical circuit components, as well as the practical analysis of both DC and AC circuits.

Course Contents:

Exp1: Verification of Ohm’s Law, Kirchhoff’s current law, and voltage law using hardware and digital simulation.

Exp2: Verification of mesh analysis using hardware and digital simulation.

Exp3: Verification of nodal analysis using hardware and digital simulation.

Exp4: Determination of average value, rms value, form factor, and peak factor of a sinusoidal wave, and square wave using hardware and digital simulation.

Exp5: Measurement of power and power factor correction.

Exp6: Verification of maximum power transfer theorem using hardware and digital simulation.

Exp7: Verification of Thevenin’s theorem using hardware and digital simulation.

Exp8: Verification of Norton’s theorem using hardware and digital simulation.

Exp9: Study of Resonance Behavior of a parallel RLC circuit with a variable capacitor.

Exp10: Study of a 3-phase system with a balanced load.

Exp11: Verification of self-inductance and mutual inductance by using hardware.

Course Learning Outcomes (CLOs):

CLO1: Familiar with DC and AC circuit analysis techniques.

CLO2: Analyze complicated circuits using different network theorems.

CLO3: Acquire skills in using PSpice/Proteus software for electrical circuit studies.

CLO4: Determine the self and mutual inductance of coupled coils.

CLO5: Demonstrate proficiency in identifying circuit components on a schematic drawing and in a lab setting.

References:

Learning Materials:

Textbooks:

1) Fundamentals of Electric circuit by Charles k. Alexander.

2) DC Electrical Circuit Analysis: A Practical Approach by James M Flore.

3) PSpice and Proteus software (Updated version).

Other Learning Materials: Journals, websites, YouTube videos.

Course Code: CSE 1236-0611

Course Title: Discrete Mathematics

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course underlies the basics in analyzing and describing objects and situations in many areas of computer science, including computer algorithms, programming languages, the art of problem-solving, cryptography, automated theorem proving, and software development.

Course Contents:

1. Sets, Proof Templates, and Induction: Basic Definitions, Operations on Sets, The Principle of Inclusion-Exclusion, and Mathematical Induction.

2. Formal Logic: Introduction to Propositional Logic, Truth and Logical Truth, Normal Forms, Predicates, and Quantification.

3. Relations: Binary Relations, Special Types of Relations, Equivalence Relations, Ordering Relations, and Relational Databases.

4. Functions: Basic Definitions, Operations on Functions, Sequences, and Subsequences, The Pigeon-Hole Principle.

5. Number Theory and Cryptography: Divisibility and Modular Arithmetic, Integer Representations and Algorithms, Primes and Greatest Common Divisors, Solving Congruences, Applications of Congruences, Cryptography.

6. Counting and Combinatorics: Traveling Salesperson’s Problem, Counting Principles, Set Decomposition Principle, Permutations and Combinations, Constructing the Kth Permutation, Counting with Repeated Objects, Combinatorial Identities.

7. Discrete Probability: Ideas of Chance in Computer Science, Cross Product Sample Spaces, Independent Events, and Conditional Probability, Discrete Random Variables, Variance, Standard Deviation, and the Law of Average.

8. Graph Theory: Introduction to Graph Theory, The Handshaking Problem, Paths and Cycles, Graph Isomorphism, Representation of Graphs, Connected Graphs, The K6nigsberg Bridge Problem

9. Trees: Definition of Trees, Spanning Trees, Rooted Trees, Directed Graphs, Application, finding a Cycle in a Directed Graph, Priority in Scheduling, Connectivity in Directed Graphs, Eulerian Circuits in Directed Graphs.

10. Analysis of Algorithms: Comparing Growth Rates of Functions, Complexity of Programs, and Uncomputability.

11. Recurrence Relations: The Tower of Hanoi Problem, Solving First-Order Recurrences Using Back Substitution, Fibonacci Recurrence Relation, Divide and Conquer Paradigm, Binary Search, Merge Sort, Multiplication of n-Bit Numbers, Divide-and-Conquer Recurrence Relations.

Course Learning Outcomes (CLOs):

CLO1: Apply basic mathematical concepts such as sets, relations, and functions using logical terminology, number theory, and counting principles.

CLO2: Able to identify problems, investigate the scenario, and define the solution such as cryptography and probabilities.

CLO3: Able to solve various problems in non-linear data structures.

CLO4: Able to solve and analyze programming challenges and software development.

References:

Learning Materials:

Textbooks:

1. Discrete Mathematics for Computer Science by Gary Haggard, John Schlipf, and Sue Whitesides

2. Discrete Mathematics & Its Applications- Kenneth H Rosen

3. Discrete Mathematics with Applications -Thomas Koshy

4. Discrete Mathematics - Seymour Lipschutz, M. Lipson, Tata McGraw Hill

5. Discrete Mathematical Structures - Kolman, Busby Ross, Prentice Hall International

6. Combinatorics: Theory and Applications - V. Krishnamurthy, East-West Press.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Discrete Mathematics

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course underlies the basics in analyzing and describing objects and situations in many areas of computer science, including computer algorithms, programming languages, the art of problem-solving, cryptography, automated theorem proving, and software development.

Course Contents:

1. Sets, Proof Templates, and Induction: Basic Definitions, Operations on Sets, The Principle of Inclusion-Exclusion, and Mathematical Induction.

2. Formal Logic: Introduction to Propositional Logic, Truth and Logical Truth, Normal Forms, Predicates, and Quantification.

3. Relations: Binary Relations, Special Types of Relations, Equivalence Relations, Ordering Relations, and Relational Databases.

4. Functions: Basic Definitions, Operations on Functions, Sequences, and Subsequences, The Pigeon-Hole Principle.

5. Number Theory and Cryptography: Divisibility and Modular Arithmetic, Integer Representations and Algorithms, Primes and Greatest Common Divisors, Solving Congruences, Applications of Congruences, Cryptography.

6. Counting and Combinatorics: Traveling Salesperson’s Problem, Counting Principles, Set Decomposition Principle, Permutations and Combinations, Constructing the Kth Permutation, Counting with Repeated Objects, Combinatorial Identities.

7. Discrete Probability: Ideas of Chance in Computer Science, Cross Product Sample Spaces, Independent Events, and Conditional Probability, Discrete Random Variables, Variance, Standard Deviation, and the Law of Average.

8. Graph Theory: Introduction to Graph Theory, The Handshaking Problem, Paths and Cycles, Graph Isomorphism, Representation of Graphs, Connected Graphs, The K6nigsberg Bridge Problem

9. Trees: Definition of Trees, Spanning Trees, Rooted Trees, Directed Graphs, Application, finding a Cycle in a Directed Graph, Priority in Scheduling, Connectivity in Directed Graphs, Eulerian Circuits in Directed Graphs.

10. Analysis of Algorithms: Comparing Growth Rates of Functions, Complexity of Programs, and Uncomputability.

11. Recurrence Relations: The Tower of Hanoi Problem, Solving First-Order Recurrences Using Back Substitution, Fibonacci Recurrence Relation, Divide and Conquer Paradigm, Binary Search, Merge Sort, Multiplication of n-Bit Numbers, Divide-and-Conquer Recurrence Relations.

Course Learning Outcomes (CLOs):

CLO1: Apply basic mathematical concepts such as sets, relations, and functions using logical terminology, number theory, and counting principles.

CLO2: Able to identify problems, investigate the scenario, and define the solution such as cryptography and probabilities.

CLO3: Able to solve various problems in non-linear data structures.

CLO4: Able to solve and analyze programming challenges and software development.

References:

Learning Materials:

Textbooks:

1. Discrete Mathematics for Computer Science by Gary Haggard, John Schlipf, and Sue Whitesides

2. Discrete Mathematics & Its Applications- Kenneth H Rosen

3. Discrete Mathematics with Applications -Thomas Koshy

4. Discrete Mathematics - Seymour Lipschutz, M. Lipson, Tata McGraw Hill

5. Discrete Mathematical Structures - Kolman, Busby Ross, Prentice Hall International

6. Combinatorics: Theory and Applications - V. Krishnamurthy, East-West Press.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: HUM 25

Course Title: Arts of Presentation

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course is designed to provide quick, natural, straightforward, and clear tactics to become a great presenter and public speaker. Art of Presentation will suit the students to become the best version of a great presenter whether they are in a presentation or public speaking class or doing a course in their major or on the job.

Course Contents:

01. Introduction to PowerPoint Presentation

06. Effective Body Language

02. Purpose of Presentation

07. Voice Control

03. Audience Assessment

08. Presenting Effectively

04. Choosing a Right topic

09. Audience Involvement

05. Rehearsal

10. Check for Understanding

Course Learning Outcomes:

At the end of the course, the student will be able to -

CLO1: Create incredible content, and deliver powerful and high-impact business presentations that audiences remember and act on.

CLO2: Simplify complex information and messages so that audiences can get easily, and remember the key messages.

CLO3: Give a presentation without notes or cue cards and overcome any possible problem from the common to the bizarre.

CLO4: Look, sound, and feel confident - as he/she has been presenting for years.

CLO5: Connect emotionally with the audience in a way that successfully persuades, influences, informs, and grabs the audience's attention right from the start and keeps it.

References:

Learning Materials:

Textbooks:

1) Impress Your Audience (Professional Presentation Skills) by H M Atif Wafik. Online version: https://www.amazon.com/Impress-Audience-Professional-Presentation-Skills-ebook/dp/B08D762XRV. The printed version is also available at “The University of Scholars” library. Journals, websites, YouTube videos

2) Powerful Presentations that Connect by Dr. Mark Johnson. Online version: https://he.kendallhunt.com/product/powerful-presentations-connect-1

3) A Speaker’s Guidebook by Dan O’Hair, Rob Stewart, and Hannah. 6th Edition.

Other Learning Materials: Journals, websites, YouTube videos.

Course Title: Arts of Presentation

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course is designed to provide quick, natural, straightforward, and clear tactics to become a great presenter and public speaker. Art of Presentation will suit the students to become the best version of a great presenter whether they are in a presentation or public speaking class or doing a course in their major or on the job.

Course Contents:

01. Introduction to PowerPoint Presentation

06. Effective Body Language

02. Purpose of Presentation

07. Voice Control

03. Audience Assessment

08. Presenting Effectively

04. Choosing a Right topic

09. Audience Involvement

05. Rehearsal

10. Check for Understanding

Course Learning Outcomes:

At the end of the course, the student will be able to -

CLO1: Create incredible content, and deliver powerful and high-impact business presentations that audiences remember and act on.

CLO2: Simplify complex information and messages so that audiences can get easily, and remember the key messages.

CLO3: Give a presentation without notes or cue cards and overcome any possible problem from the common to the bizarre.

CLO4: Look, sound, and feel confident - as he/she has been presenting for years.

CLO5: Connect emotionally with the audience in a way that successfully persuades, influences, informs, and grabs the audience's attention right from the start and keeps it.

References:

Learning Materials:

Textbooks:

1) Impress Your Audience (Professional Presentation Skills) by H M Atif Wafik. Online version: https://www.amazon.com/Impress-Audience-Professional-Presentation-Skills-ebook/dp/B08D762XRV. The printed version is also available at “The University of Scholars” library. Journals, websites, YouTube videos

2) Powerful Presentations that Connect by Dr. Mark Johnson. Online version: https://he.kendallhunt.com/product/powerful-presentations-connect-1

3) A Speaker’s Guidebook by Dan O’Hair, Rob Stewart, and Hannah. 6th Edition.

Other Learning Materials: Journals, websites, YouTube videos.

Course Code: MATH-2115-0541

Course Title: Mathematics-III

Course Type: Theory

Prerequisite: MATH 1203-0541

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

Differential equations are used to modal and analyze many physical phenomena in various engineering and science as well as medical disciplines. Fourier Transform is a useful tool for decomposing images into sine and cosine components and also frequency domains. This course is designed to provide theoretical knowledge regarding the formation and solution techniques of differential equations using different methods and Laplace transformation, and Fourier transformations.

Course Contents:

1. Ordinary Differential Equations (ODE): Formation of the ordinary differential equation, Solutions of first order ordinary differential equations using different methods, Solution of second and higher orders differential equations and their applications; Solution of differential equations of higher order when dependent and independent variables are absent; Solution of differential equation by the method based on factorization of operators.

2. Partial Differential Equations (PDE): Formation of partial differential equations, Solution of linear and non-linear partial differential equations; Wave equations; Particular solution with boundary and initial conditions.

3. Fourier transformations (FT): Fourier series, Fourier integral, complex form of the Fourier series, Parseval’s formula, Fourier transforms and their application in solving boundary value problems of wave equations.

4. Laplace Transforms (LT): Laplace transforms of elementary functions and their applications, Inverse Laplace transforms, Laplace transforms of ordinary and Partial differentiation, Solution of differential equations by Laplace transforms, and Evaluation of improper integrals.

Course Learning Outcomes (CLOs):

CLO1: Able to understand fundamentals and formation of ordinary and partial differential equations, Fourier and Laplace transformations.

CLO2: Analyze properties of different model problems based on ordinary and partial differential equations, Fourier and Laplace transformations.

CLO3: Solve mathematical problems relating ordinary and partial differential equations, Fourier and Laplace transformations.

CLO4: Apply acquired knowledge in real-life problems like dynamics, electric circuits, propagation of heat or sound or image or frequency domain and population growth analysis, etc.

CLO5: Develop new models in various engineering and science as well as medical disciplines.

References:

Learning Materials:

Textbooks:

1. Ross, S.L. 2002. Differential Equations, 3rded, Wiley & Sons, NY.

2. Sharma, B.D. 2003. Differential Equations, 7thed, Kedar Nath Ram Nath, Meerut.

3. Simmons, G.F. 1999. Differential Equations, 2nded, TMH, New Delhi.

4. Dennemeyer, R. 1998. Introduction to Partial Differential Equations, 9thed, McGraw-Hill, NY.

5. Spiegel, M R. 1974. Fourier Analysis 1sted, McGraw-Hill Co., New Delhi.

6. Spiegel, M R. 1995. Laplace Transforms, 1sted, McGraw-Hill Co., New Delhi

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Mathematics-III

Course Type: Theory

Prerequisite: MATH 1203-0541

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

Differential equations are used to modal and analyze many physical phenomena in various engineering and science as well as medical disciplines. Fourier Transform is a useful tool for decomposing images into sine and cosine components and also frequency domains. This course is designed to provide theoretical knowledge regarding the formation and solution techniques of differential equations using different methods and Laplace transformation, and Fourier transformations.

Course Contents:

1. Ordinary Differential Equations (ODE): Formation of the ordinary differential equation, Solutions of first order ordinary differential equations using different methods, Solution of second and higher orders differential equations and their applications; Solution of differential equations of higher order when dependent and independent variables are absent; Solution of differential equation by the method based on factorization of operators.

2. Partial Differential Equations (PDE): Formation of partial differential equations, Solution of linear and non-linear partial differential equations; Wave equations; Particular solution with boundary and initial conditions.

3. Fourier transformations (FT): Fourier series, Fourier integral, complex form of the Fourier series, Parseval’s formula, Fourier transforms and their application in solving boundary value problems of wave equations.

4. Laplace Transforms (LT): Laplace transforms of elementary functions and their applications, Inverse Laplace transforms, Laplace transforms of ordinary and Partial differentiation, Solution of differential equations by Laplace transforms, and Evaluation of improper integrals.

Course Learning Outcomes (CLOs):

CLO1: Able to understand fundamentals and formation of ordinary and partial differential equations, Fourier and Laplace transformations.

CLO2: Analyze properties of different model problems based on ordinary and partial differential equations, Fourier and Laplace transformations.

CLO3: Solve mathematical problems relating ordinary and partial differential equations, Fourier and Laplace transformations.

CLO4: Apply acquired knowledge in real-life problems like dynamics, electric circuits, propagation of heat or sound or image or frequency domain and population growth analysis, etc.

CLO5: Develop new models in various engineering and science as well as medical disciplines.

References:

Learning Materials:

Textbooks:

1. Ross, S.L. 2002. Differential Equations, 3rded, Wiley & Sons, NY.

2. Sharma, B.D. 2003. Differential Equations, 7thed, Kedar Nath Ram Nath, Meerut.

3. Simmons, G.F. 1999. Differential Equations, 2nded, TMH, New Delhi.

4. Dennemeyer, R. 1998. Introduction to Partial Differential Equations, 9thed, McGraw-Hill, NY.

5. Spiegel, M R. 1974. Fourier Analysis 1sted, McGraw-Hill Co., New Delhi.

6. Spiegel, M R. 1995. Laplace Transforms, 1sted, McGraw-Hill Co., New Delhi

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: EEE 2113-0714

Course Title: Electronic Devices & Circuit

Course Type: Theory

Prerequisite: EEE-1211-0714

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

This course is designed to provide fundamental concepts of electronic devices like a diode, Bipolar junction transistor, MOSFET, and Operational amplifiers. The understanding of these electronic devices is significant to design and analyze significant electronic circuits that are used in day-to-day life applications.

Course Contents:

1. P-N junction as a circuit element: Intrinsic and extrinsic semiconductors, operational principle of p-n junction diode, current-voltage characteristics of a diode, simplified dc and ac diode models, dynamic resistance, and capacitance.

2. Diode circuits: Half wave and full wave bridge rectifiers, rectifiers with filter capacitor, characteristics of a Zener diode and its applications. Zener shunt regulator.

3. Bipolar junction transistor (BJT) as a circuit element: Basic structure. BJT characteristics and regions of operation, DC analysis, basic transistor applications, biasing the BJT for discrete circuits, basic transistor applications, CE amplifiers, AC load lines, CC and CB amplifiers, small signal equivalent circuit models, BJT as a switch. Single stage BJT amplifier circuits and their configurations: Voltage and current gain, input and output resistances. RC coupled two-stage BJT amplifiers.

4. Metal-Oxide-Semiconductor Field-Effect-Transistor (MOSFET) as circuit element: structure and physical operation of MOSFETs, body effect, current-voltage characteristics of MOSFETs, Early Effect, biasing discrete and integrated MOS amplifier circuits, single stage MOS amplifiers. Introduction to operational amplifiers and op-amp circuits. Op-amp applications: inverting amplifier, non-inverting amplifier, summing amplifier, differential amplifier, logarithmic amplifier, differentiator, integrator, voltage to current converter, voltage follower. Classification, and analysis of feedback amplifier.

5. Sinusoidal oscillators: Concept and its classification. Active filters, Passive Filters: basic types. Characteristic impedance and attenuation, ladder network. Negative impedance converters. Wave shaping: Linear and non-linear waveshaping, Clipping and Clamping circuits, Non-Linear function circuits. Negative resistance switching circuits. Timing circuits; Bi-stable, mono-stable, and stable multi vibrators, Sweep and staircase generator, IC 555 and its application.

Course Learning Outcomes (CLOs):

CLO1: Explain the operation principle and terminal characteristics of the diode, transistors, MOSFET, and Op-amps.

CLO2: Compare the different characteristics of diodes, transistors, MOSFET, and op-amp.

CLO3: Analyze the performance of those devices and their biasing circuits.

CLO4: Solve real-world engineering problems including rectification, switching, amplification, and timing circuit using knowledge of semiconductor diodes and transistors.

References:

Learning Materials:

1. Operational Amplifiers and Linear Integrated Circuits, Robert F. Coughlin, Frederick F. Driscoll

2. Integrated Electronics: Analog and Digital Circuits and Systems, J. Millman, C. Halkias, C. D Parikh

3. Microelectronic Circuits, Adel S. Sedra, Kenneth C. Smith

4. Electronic Devices and Circuit Theory, R. Boyelstad, L. Nashelsky

Course Title: Electronic Devices & Circuit

Course Type: Theory

Prerequisite: EEE-1211-0714

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

This course is designed to provide fundamental concepts of electronic devices like a diode, Bipolar junction transistor, MOSFET, and Operational amplifiers. The understanding of these electronic devices is significant to design and analyze significant electronic circuits that are used in day-to-day life applications.

Course Contents:

1. P-N junction as a circuit element: Intrinsic and extrinsic semiconductors, operational principle of p-n junction diode, current-voltage characteristics of a diode, simplified dc and ac diode models, dynamic resistance, and capacitance.

2. Diode circuits: Half wave and full wave bridge rectifiers, rectifiers with filter capacitor, characteristics of a Zener diode and its applications. Zener shunt regulator.

3. Bipolar junction transistor (BJT) as a circuit element: Basic structure. BJT characteristics and regions of operation, DC analysis, basic transistor applications, biasing the BJT for discrete circuits, basic transistor applications, CE amplifiers, AC load lines, CC and CB amplifiers, small signal equivalent circuit models, BJT as a switch. Single stage BJT amplifier circuits and their configurations: Voltage and current gain, input and output resistances. RC coupled two-stage BJT amplifiers.

4. Metal-Oxide-Semiconductor Field-Effect-Transistor (MOSFET) as circuit element: structure and physical operation of MOSFETs, body effect, current-voltage characteristics of MOSFETs, Early Effect, biasing discrete and integrated MOS amplifier circuits, single stage MOS amplifiers. Introduction to operational amplifiers and op-amp circuits. Op-amp applications: inverting amplifier, non-inverting amplifier, summing amplifier, differential amplifier, logarithmic amplifier, differentiator, integrator, voltage to current converter, voltage follower. Classification, and analysis of feedback amplifier.

5. Sinusoidal oscillators: Concept and its classification. Active filters, Passive Filters: basic types. Characteristic impedance and attenuation, ladder network. Negative impedance converters. Wave shaping: Linear and non-linear waveshaping, Clipping and Clamping circuits, Non-Linear function circuits. Negative resistance switching circuits. Timing circuits; Bi-stable, mono-stable, and stable multi vibrators, Sweep and staircase generator, IC 555 and its application.

Course Learning Outcomes (CLOs):

CLO1: Explain the operation principle and terminal characteristics of the diode, transistors, MOSFET, and Op-amps.

CLO2: Compare the different characteristics of diodes, transistors, MOSFET, and op-amp.

CLO3: Analyze the performance of those devices and their biasing circuits.

CLO4: Solve real-world engineering problems including rectification, switching, amplification, and timing circuit using knowledge of semiconductor diodes and transistors.

References:

Learning Materials:

1. Operational Amplifiers and Linear Integrated Circuits, Robert F. Coughlin, Frederick F. Driscoll

2. Integrated Electronics: Analog and Digital Circuits and Systems, J. Millman, C. Halkias, C. D Parikh

3. Microelectronic Circuits, Adel S. Sedra, Kenneth C. Smith

4. Electronic Devices and Circuit Theory, R. Boyelstad, L. Nashelsky

Course Code: CSE 2114-0714

Course Title: Electronic Devices & Circuits Lab

Course Type: Lab

Prerequisite: EEE-1212-0714

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

To learn and familiarize the basic concepts of electronic components practically and analyze the electronic circuit practically. By the end of the course, students will be able to learn about IC used in the building up and developing of any required circuit. Besides, students will also be able to learn to generate the desired output of any electronic circuit.

Lab Tasks:

Exp: 01: I-V Characteristics of the diode.

Exp: 02: Diode rectifier circuits.

Exp: 03: Clipper and Clamper circuits.

Exp: 04: Zener Diode applications.

Exp: 05: The output characteristics of CE (common emitter) configuration of BJT.

Exp: 06: The BJT Biasing Circuits.

Exp: 07: Frequency Response of a CE (Common Emitter) Amplifier Circuit and measurement of Input and Output Impedance.

Exp: 08: Study of an R- C Phase Shift Oscillator

Exp: 09: The I - V Characteristics of an N - Channel Enhancement type MOSFET.

Exp: 10: Study of an R- C Phase Shift Oscillator

Exp: 11: Mathematical operations using OPAMP

Exp: 12: Study of high pass and low pass filters using Op-amp.

Course Learning Outcomes (CLOs):

At the end of the course, the students would be able to:

CLO1: Compare basic theoretical results with experimental results of various semiconductor devices.

CLO2: Explain how to design diode circuits, BJT, MOSFET, and operational amplifier circuits from a set of specifications.

CLO3: Able to design electronic projects.

References:

Learning Materials:

1. Operational Amplifiers and Linear Integrated Circuits, Robert F. Coughlin, Frederick F. Driscoll

2. Integrated Electronics: Analog and Digital Circuits and Systems, J. Millman, C. Halkias, C. D Parikh

3. Microelectronic Circuits, Adel S. Sedra, Kenneth C. Smith

4. Electronic Devices and Circuit Theory, R. Boyelstad, L. Nashelsky

Course Title: Electronic Devices & Circuits Lab

Course Type: Lab

Prerequisite: EEE-1212-0714

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

To learn and familiarize the basic concepts of electronic components practically and analyze the electronic circuit practically. By the end of the course, students will be able to learn about IC used in the building up and developing of any required circuit. Besides, students will also be able to learn to generate the desired output of any electronic circuit.

Lab Tasks:

Exp: 01: I-V Characteristics of the diode.

Exp: 02: Diode rectifier circuits.

Exp: 03: Clipper and Clamper circuits.

Exp: 04: Zener Diode applications.

Exp: 05: The output characteristics of CE (common emitter) configuration of BJT.

Exp: 06: The BJT Biasing Circuits.

Exp: 07: Frequency Response of a CE (Common Emitter) Amplifier Circuit and measurement of Input and Output Impedance.

Exp: 08: Study of an R- C Phase Shift Oscillator

Exp: 09: The I - V Characteristics of an N - Channel Enhancement type MOSFET.

Exp: 10: Study of an R- C Phase Shift Oscillator

Exp: 11: Mathematical operations using OPAMP

Exp: 12: Study of high pass and low pass filters using Op-amp.

Course Learning Outcomes (CLOs):

At the end of the course, the students would be able to:

CLO1: Compare basic theoretical results with experimental results of various semiconductor devices.

CLO2: Explain how to design diode circuits, BJT, MOSFET, and operational amplifier circuits from a set of specifications.

CLO3: Able to design electronic projects.

References:

Learning Materials:

1. Operational Amplifiers and Linear Integrated Circuits, Robert F. Coughlin, Frederick F. Driscoll

2. Integrated Electronics: Analog and Digital Circuits and Systems, J. Millman, C. Halkias, C. D Parikh

3. Microelectronic Circuits, Adel S. Sedra, Kenneth C. Smith

4. Electronic Devices and Circuit Theory, R. Boyelstad, L. Nashelsky

Course Code: CSE 1111-0611

Course Title: Fundamentals of Computer and Office Applications

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hour: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

The changing and emerging demand of digitization, continuous improvisation of technology, and advancement of new organizational and internal improvements are touching our lives in almost all spheres. So, to adapt to the latest challenge, the necessity of computers needs no bounds. Introduction to Computer Application is one of the prominent core courses to introduce the basic utilization and most recent technology of computers which is designed for students with little knowledge of computers.

Course Contents:

1. Fundamentals of Computer: Introduction to Computer, Functionalities, History, Advantages, Disadvantages, Architecture, Characteristics, Application, Types, Basic Components.

2. Number Systems: Introduction to Number System, Conversion of Different Number Systems, Classification, and Types of Number System

3. Hardware and Software: Introduction, Computer Memory, Peripherals, Input Devices, Output Devices, Software, and Requirements.

4. Operating System: Features, Comparison, Windows installation, Activating and Security features, User Accounts, Getting Help, Characteristics.

5. Memory: Primary Memory, Secondary Memory, Characteristics, Advantages, Disadvantages

6. MS Office Fundamentals: Introduction to MS Word, MS Excel, MS Powerpoint, Windows Interface, Word Application, Viewing Documents, Basic and Advanced Formatting, navigating through a Word Document, Printing Documents, Preview, Workbook, Worksheet, Formatting, Advanced formatting, printing worksheets, Creating Presentations, Basic and Advanced Formatting, Using Templates, Inserting charts and tables.

7. Security and Networking: Introduction to security and networking, Data and Information, File Sharing, Internet Services, and p2p Networking.

Course Learning Outcomes (CLOs):

CLO1: Able to recognize the most up-to-date and recent emerging discipline of technology.

CLO2: Able to Demonstrate the basic knowledge of computer nomenclature, particularly with respect to a personal computer, Hardware, Software, Characteristics of Information Technology, Web, and Enterprise Computing.

CLO3: Learn to differentiate between data and information, input and output devices, system and application software, and primary and secondary storage.

CLO4: Competent to perform data representation and work with different number systems and certain computer configurations based on specified organization and personal needs.

CLO5: Able to understand the resources for secure information systems focusing on both human and technological safeguards and also able to understand how information systems raise ethical concerns in society, and how they influence crime.

References:

Learning Materials:

Textbooks:

1. Computer Fundamentals (7th Edition) – Peter Norton, McGraw Hill Education (2017).

2. The Complete PC Upgrade and Maintenance Guide (16th Edition) – Mark Minasi, Sybex (2005).

3. Computer Fundamentals and ICT by M. LutfarRahman , M. Shamim Kaiser , M. Ariful Rahman , M. Alamgir Hossain.

4. Computer Fundamentals by Pradeep K. Sinha, 6th Edition.

5. Introduction to Information System by James A. O’Brien, 8th Edition.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Fundamentals of Computer and Office Applications

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hour: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

The changing and emerging demand of digitization, continuous improvisation of technology, and advancement of new organizational and internal improvements are touching our lives in almost all spheres. So, to adapt to the latest challenge, the necessity of computers needs no bounds. Introduction to Computer Application is one of the prominent core courses to introduce the basic utilization and most recent technology of computers which is designed for students with little knowledge of computers.

Course Contents:

1. Fundamentals of Computer: Introduction to Computer, Functionalities, History, Advantages, Disadvantages, Architecture, Characteristics, Application, Types, Basic Components.

2. Number Systems: Introduction to Number System, Conversion of Different Number Systems, Classification, and Types of Number System

3. Hardware and Software: Introduction, Computer Memory, Peripherals, Input Devices, Output Devices, Software, and Requirements.

4. Operating System: Features, Comparison, Windows installation, Activating and Security features, User Accounts, Getting Help, Characteristics.

5. Memory: Primary Memory, Secondary Memory, Characteristics, Advantages, Disadvantages

6. MS Office Fundamentals: Introduction to MS Word, MS Excel, MS Powerpoint, Windows Interface, Word Application, Viewing Documents, Basic and Advanced Formatting, navigating through a Word Document, Printing Documents, Preview, Workbook, Worksheet, Formatting, Advanced formatting, printing worksheets, Creating Presentations, Basic and Advanced Formatting, Using Templates, Inserting charts and tables.

7. Security and Networking: Introduction to security and networking, Data and Information, File Sharing, Internet Services, and p2p Networking.

Course Learning Outcomes (CLOs):

CLO1: Able to recognize the most up-to-date and recent emerging discipline of technology.

CLO2: Able to Demonstrate the basic knowledge of computer nomenclature, particularly with respect to a personal computer, Hardware, Software, Characteristics of Information Technology, Web, and Enterprise Computing.

CLO3: Learn to differentiate between data and information, input and output devices, system and application software, and primary and secondary storage.

CLO4: Competent to perform data representation and work with different number systems and certain computer configurations based on specified organization and personal needs.

CLO5: Able to understand the resources for secure information systems focusing on both human and technological safeguards and also able to understand how information systems raise ethical concerns in society, and how they influence crime.

References:

Learning Materials:

Textbooks:

1. Computer Fundamentals (7th Edition) – Peter Norton, McGraw Hill Education (2017).

2. The Complete PC Upgrade and Maintenance Guide (16th Edition) – Mark Minasi, Sybex (2005).

3. Computer Fundamentals and ICT by M. LutfarRahman , M. Shamim Kaiser , M. Ariful Rahman , M. Alamgir Hossain.

4. Computer Fundamentals by Pradeep K. Sinha, 6th Edition.

5. Introduction to Information System by James A. O’Brien, 8th Edition.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 1112-0611

Course Title: Fundamentals of Computer Lab

Course Type: Lab

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

This course provides a basic introduction to computers along with basic application and programming concepts and to teach and introduce students to the modern technological amenities that address how they work and how to use them

Course Contents:

Lab tasks:

⮚ Introduction and Identification of major computational components and Hardware Parts of PC (Monitor Hard Drive, RAM, ROM, Microprocessor, Motherboard, BIOS Battery, Chip, Ports, Mouse, Keyboard, Data Cord, etc.)

⮚ Introduction to Application Software through MS Office Applications (MS Word 2013)

⮚ Introduction to Application Software through MS Office Applications (MS Excel 2013)

⮚ Introduction to Application Software through MS Office Applications (MS PowerPoint 2013, Making a good PowerPoint Presentation)

⮚ Understand the basic concept of different Programming Languages

⮚ Understand the fundamental concept of Compiler and Interpreter.

⮚ Understand the fundamental concept of Flow Charts and algorithms.

⮚ Introduction to System Software (Various Operating Systems)

⮚ Introduction to Network, Security System,s and Cyber Crime

⮚ Understand the Introduction and Utilization of Cloud Storage.

Course Learning Outcomes (CLOs):

CLO1: Able to apply different tools and components regarding computer hardware and software.

CLO2: Competent to use Microsoft Office Applications Word, Excel, Access, and Powerpoint by hands-on use.

CLO3: Able to learn a handful of various fundamental concepts of programming language, compiler, and interpreter.

CLO4: Able to understand the fundamental concept of networking, security system, cybercrime, and ethical issues.

Course Title: Fundamentals of Computer Lab

Course Type: Lab

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

This course provides a basic introduction to computers along with basic application and programming concepts and to teach and introduce students to the modern technological amenities that address how they work and how to use them

Course Contents:

Lab tasks:

⮚ Introduction and Identification of major computational components and Hardware Parts of PC (Monitor Hard Drive, RAM, ROM, Microprocessor, Motherboard, BIOS Battery, Chip, Ports, Mouse, Keyboard, Data Cord, etc.)

⮚ Introduction to Application Software through MS Office Applications (MS Word 2013)

⮚ Introduction to Application Software through MS Office Applications (MS Excel 2013)

⮚ Introduction to Application Software through MS Office Applications (MS PowerPoint 2013, Making a good PowerPoint Presentation)

⮚ Understand the basic concept of different Programming Languages

⮚ Understand the fundamental concept of Compiler and Interpreter.

⮚ Understand the fundamental concept of Flow Charts and algorithms.

⮚ Introduction to System Software (Various Operating Systems)

⮚ Introduction to Network, Security System,s and Cyber Crime

⮚ Understand the Introduction and Utilization of Cloud Storage.

Course Learning Outcomes (CLOs):

CLO1: Able to apply different tools and components regarding computer hardware and software.

CLO2: Competent to use Microsoft Office Applications Word, Excel, Access, and Powerpoint by hands-on use.

CLO3: Able to learn a handful of various fundamental concepts of programming language, compiler, and interpreter.

CLO4: Able to understand the fundamental concept of networking, security system, cybercrime, and ethical issues.

Course Code: CSE 2121–0613

Course Title: System Analysis and Design

Course Type: Theory

Pre-requisite: CSE 1213-0613

Credits:3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

This course covers information systems principles, including research and design. Students will study data requirements gathering and analysis strategies and data modeling approaches. The course will also deliver about the relevance and restrictions placed by the domain of the information system and the business principles governing the design and, as part of the requirements analysis, it considered functional dependencies and domain normalization. This course will explore the modeling of object-oriented information systems.

Course Contents:

1. Fundamentals of system analysis: includes systems, roles, and development approaches; Understanding and simulating organizational structure; Project management.

2. Information gathering and requirements analysis: Methodologies for modernizing system development (Interactive methods; Unobtrusive methods; agile modeling and prototyping; )

3. The analysis process: Professional obligations about quality assurance and reporting and how they must be considered during all phases of software development (Using data flow diagrams; Analyzing systems using data dictionaries; Process specifications and structured decisions; Object-oriented systems analysis and design using UML)

4. The essentials of design: Designing effective output, designing practical input; Designing databases; Human-computer interaction; Unified Modeling Language (UML) models, requirements elicitation, analysis, and implementation of information systems and accompanying software are performed.

5. Quality assurance and implementation: Evaluation of information system viability and the relationship between and the system's consequences on its users. (Designing proper data entry procedures; Quality assurance and performance)

Course Learning Outcomes (CLOs):

CLO1: A solid foundation for comprehending a systems development project's life cycle to be able to explain the process of systems analysis and design.

CLO2: Analyze and contrast the many different approaches that are utilized in the process of studying and improving organizational systems.

CLO3: As a systems analyst, be able to compare and contrast the challenges that technology managers encounter with regard to the decision-making process.

CLO4: Competent to give an explanation of the most fundamental problems that technology managers face during the process of putting systems designs into action.

References:

Learning Materials:

Textbooks:

1. Elias M. Awad, Systems Analysis and Design, Published by Galgotia Publications Pvt Ltd, 2nd Edition.

2. I. T. Hawryszkiewycz, Introduction to Systems Analysis and Design, Published by Prentice Hall of India, 3rd Edition.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: System Analysis and Design

Course Type: Theory

Pre-requisite: CSE 1213-0613

Credits:3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

This course covers information systems principles, including research and design. Students will study data requirements gathering and analysis strategies and data modeling approaches. The course will also deliver about the relevance and restrictions placed by the domain of the information system and the business principles governing the design and, as part of the requirements analysis, it considered functional dependencies and domain normalization. This course will explore the modeling of object-oriented information systems.

Course Contents:

1. Fundamentals of system analysis: includes systems, roles, and development approaches; Understanding and simulating organizational structure; Project management.

2. Information gathering and requirements analysis: Methodologies for modernizing system development (Interactive methods; Unobtrusive methods; agile modeling and prototyping; )

3. The analysis process: Professional obligations about quality assurance and reporting and how they must be considered during all phases of software development (Using data flow diagrams; Analyzing systems using data dictionaries; Process specifications and structured decisions; Object-oriented systems analysis and design using UML)

4. The essentials of design: Designing effective output, designing practical input; Designing databases; Human-computer interaction; Unified Modeling Language (UML) models, requirements elicitation, analysis, and implementation of information systems and accompanying software are performed.

5. Quality assurance and implementation: Evaluation of information system viability and the relationship between and the system's consequences on its users. (Designing proper data entry procedures; Quality assurance and performance)

Course Learning Outcomes (CLOs):

CLO1: A solid foundation for comprehending a systems development project's life cycle to be able to explain the process of systems analysis and design.

CLO2: Analyze and contrast the many different approaches that are utilized in the process of studying and improving organizational systems.

CLO3: As a systems analyst, be able to compare and contrast the challenges that technology managers encounter with regard to the decision-making process.

CLO4: Competent to give an explanation of the most fundamental problems that technology managers face during the process of putting systems designs into action.

References:

Learning Materials:

Textbooks:

1. Elias M. Awad, Systems Analysis and Design, Published by Galgotia Publications Pvt Ltd, 2nd Edition.

2. I. T. Hawryszkiewycz, Introduction to Systems Analysis and Design, Published by Prentice Hall of India, 3rd Edition.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 2122-0613

Course Title: System Analysis and Design Lab

Course Type: Lab

Pre-requisite: CSE 1214-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

Students gain practical experience in requirements elicitation and modeling and systems analysis and feasibility assessment as part of a system development project to establish an event-driven information system. They also gain practical experience using a CASE tool to construct object and class definitions and create models.

Course Contents:

➢ Aim to acquire accurate data from the proposed system's intended user.

➢ Demonstrate methods and instruments for acquiring data

➢ Identify procedure Description Tools and technical tool conversion from specification

➢ Perform analysis of Alternative Solution Using Objective, Sub Objective, and Shortcoming

➢ Documenting calculation and analysis of costs and benefits of the proposed system.

➢ Create a Feasibility Report.

➢ Create a Proposal Structure for a System.

➢ Develop the solution for the proposed system.

➢ Make the Input Design and the Output Design, as well as the File and the Database Design, File Architecture, File Maintenance

➢ Demonstrate the goals of Quality Control and Assurance

➢ Analyze Digital Marketing: The Advantages of Direct Interaction for the End User,

Course Learning Outcomes (CLOs):

CLO1: Acknowledge project management methods.

CLO2: Learn to create business documents that contain relevant content that is well-organized, show professionalism, and adhere to conventional business English standards.

CLO3: Competent to work alongside and lead teams in a variety of settings.

CLO4: Able to solve information systems challenges, and use the right tools and approaches from the field of information systems.

CLO5: Able to generate different ideas that are related to the models, methods, and procedures that are utilized in the process of system analysis and design.

Course Title: System Analysis and Design Lab

Course Type: Lab

Pre-requisite: CSE 1214-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

Students gain practical experience in requirements elicitation and modeling and systems analysis and feasibility assessment as part of a system development project to establish an event-driven information system. They also gain practical experience using a CASE tool to construct object and class definitions and create models.

Course Contents:

➢ Aim to acquire accurate data from the proposed system's intended user.

➢ Demonstrate methods and instruments for acquiring data

➢ Identify procedure Description Tools and technical tool conversion from specification

➢ Perform analysis of Alternative Solution Using Objective, Sub Objective, and Shortcoming

➢ Documenting calculation and analysis of costs and benefits of the proposed system.

➢ Create a Feasibility Report.

➢ Create a Proposal Structure for a System.

➢ Develop the solution for the proposed system.

➢ Make the Input Design and the Output Design, as well as the File and the Database Design, File Architecture, File Maintenance

➢ Demonstrate the goals of Quality Control and Assurance

➢ Analyze Digital Marketing: The Advantages of Direct Interaction for the End User,

Course Learning Outcomes (CLOs):

CLO1: Acknowledge project management methods.

CLO2: Learn to create business documents that contain relevant content that is well-organized, show professionalism, and adhere to conventional business English standards.

CLO3: Competent to work alongside and lead teams in a variety of settings.

CLO4: Able to solve information systems challenges, and use the right tools and approaches from the field of information systems.

CLO5: Able to generate different ideas that are related to the models, methods, and procedures that are utilized in the process of system analysis and design.

Course Code: CE-2144-0611

Course Title: Engineering Drawing

Course Type: Lab

Prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course is designed to teach the basic concepts and implementation of Engineering Drawing, including visualization, graphics theory, drawing standards, and conventions, drawing tools, as well as how to use 2D and 3D drawings in engineering applications.

Course Contents:

➢ Introduction to Engineering Drawing,

➢ Importance of Engineering Drawing,

➢ Drawing Techniques: Manual and Computer Aided Drawing (CAD),

➢ Drawing Instruments and their uses.

➢ Conventions in drawing – lettering – BIS conventions. Dimensioning rules, geometrical construction.

➢ Draw Engineering Curves, Orthographic and Isometric projections using AutoCAD.

➢ Project

Course Learning Outcomes (CLOs):

CLO1: Able to know the basics of engineering drawing, drawing tools, and their importance.

CLO2: Analyze problems and design various curves in real life.

CLO3: Design the Orthographic and Isometric projections using advanced tools like AutoCAD.

References:

Learning Materials:

Textbooks:

1. Narayana K.L, Kannaiah P, Engineering Drawing, Scitech publications, (2017).

2 Venugopal K., Engineering Drawing, New Age International, (2004)

3 Bhatt N.D., Engineering Drawing, Charotar Publishing House, (2000).

4 Dhananjay A Jolhe, Engineering drawing, TMH, 2008.

5 W J Luzadder and J M Duff, Fundamentals of Engineering Drawing, 11th edition, Prentice-Hall of India, 1995.

Other Learning Materials: Web Materials, etc.

1. https://iastate.pressbooks.pub/visualgraphiccomm/chapter/chapter-1/

2. https://gencor.in/autocad-syllabus/

3. https://www.slideshare.net/retouchreform/autocad-training-syllabus

Course Title: Engineering Drawing

Course Type: Lab

Prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 1

Semester/Term: 2

Rationale:

This course is designed to teach the basic concepts and implementation of Engineering Drawing, including visualization, graphics theory, drawing standards, and conventions, drawing tools, as well as how to use 2D and 3D drawings in engineering applications.

Course Contents:

➢ Introduction to Engineering Drawing,

➢ Importance of Engineering Drawing,

➢ Drawing Techniques: Manual and Computer Aided Drawing (CAD),

➢ Drawing Instruments and their uses.

➢ Conventions in drawing – lettering – BIS conventions. Dimensioning rules, geometrical construction.

➢ Draw Engineering Curves, Orthographic and Isometric projections using AutoCAD.

➢ Project

Course Learning Outcomes (CLOs):

CLO1: Able to know the basics of engineering drawing, drawing tools, and their importance.

CLO2: Analyze problems and design various curves in real life.

CLO3: Design the Orthographic and Isometric projections using advanced tools like AutoCAD.

References:

Learning Materials:

Textbooks:

1. Narayana K.L, Kannaiah P, Engineering Drawing, Scitech publications, (2017).

2 Venugopal K., Engineering Drawing, New Age International, (2004)

3 Bhatt N.D., Engineering Drawing, Charotar Publishing House, (2000).

4 Dhananjay A Jolhe, Engineering drawing, TMH, 2008.

5 W J Luzadder and J M Duff, Fundamentals of Engineering Drawing, 11th edition, Prentice-Hall of India, 1995.

Other Learning Materials: Web Materials, etc.

1. https://iastate.pressbooks.pub/visualgraphiccomm/chapter/chapter-1/

2. https://gencor.in/autocad-syllabus/

3. https://www.slideshare.net/retouchreform/autocad-training-syllabus

Course Code: CSE 2105-0613

Course Title: Competitive Programming-I

Course Type: Lab

Prerequisite: CSE 1111-0613, CSE 1213-0613

Credits: 1

Contact Hours:

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

Upon knowing the basic structured programming language this course focuses on problem-solving using basic knowledge and prepares students for competitive programming. Through the problem-solving process, one can manifest their language skill as well as efficient use of syntax and grapes a real-life experience of programming.

Course Contents:

1. Introduction to Competitive Programming: History and background, Different problem-solving platforms, Languages, Tools for a problem-solving, Career path

2. Data types and Input-Output: Different data types, Problem wise data type selection, taking input in different forms, Showing output in complex forms.

3. Conditional logic: if-else, switch case, ternary operator, Basic problem solving from online judges

Basic Contest - 01;

4. Loops: For loop, while loop, do-while loop, for each loop, nested loop, auto keyword, Problem-solving

Basic contest - 02;

5. Integer array: Array manipulation and operations

6. Complexity Analysis: Time complexity, Space complexity, Code optimization

7. Functions: Return type, arguments, parameters, pass-by references

Basic Contest - 03:

8. Pointer: Introduction to a pointer, memory address, references, dynamic memory allocation, malloc(), calloc(), realloc()

9. String/ Character array: character array, character pointer, string manipulation

Basic Contest- 04:

10. Sorting: Linear sorting, library functions for sorting Long contest on array and string

Course Learning Outcomes (CLOs):

CLO1: Able to improve thinking and reasoning skills in different courses and competitions.

CLO2: Able to operate different data types, conditional logic, and loops and gain the competitive mindset to build problem-solving skills.

CLO3: Able to analyze time and space complexity and optimize code, demonstrate problem-solving skills to different platforms.

CLO4: Competent performing teamwork, interacting with programming solving community, learning strategic planning of problem setting community and style of international standard of problem-solving to adapt the new emerging technologies.

References:

Learning Materials:

Textbooks:

1. The C Programming Language. 2nd Edition Book, Brian Kernighan and Dennis Ritchie

2. Competitive Programmer’s Handbook, Antti Laaksonen

3. Competitive Programming 4: The Lower Bound of Programming Contests, Steven Halim, Felix Halim, Suhendry Effendy

Other Learning Materials: Problem-solving platforms, Webinars, Web Materials, etc.

Course Title: Competitive Programming-I

Course Type: Lab

Prerequisite: CSE 1111-0613, CSE 1213-0613

Credits: 1

Contact Hours:

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

Upon knowing the basic structured programming language this course focuses on problem-solving using basic knowledge and prepares students for competitive programming. Through the problem-solving process, one can manifest their language skill as well as efficient use of syntax and grapes a real-life experience of programming.

Course Contents:

1. Introduction to Competitive Programming: History and background, Different problem-solving platforms, Languages, Tools for a problem-solving, Career path

2. Data types and Input-Output: Different data types, Problem wise data type selection, taking input in different forms, Showing output in complex forms.

3. Conditional logic: if-else, switch case, ternary operator, Basic problem solving from online judges

Basic Contest - 01;

4. Loops: For loop, while loop, do-while loop, for each loop, nested loop, auto keyword, Problem-solving

Basic contest - 02;

5. Integer array: Array manipulation and operations

6. Complexity Analysis: Time complexity, Space complexity, Code optimization

7. Functions: Return type, arguments, parameters, pass-by references

Basic Contest - 03:

8. Pointer: Introduction to a pointer, memory address, references, dynamic memory allocation, malloc(), calloc(), realloc()

9. String/ Character array: character array, character pointer, string manipulation

Basic Contest- 04:

10. Sorting: Linear sorting, library functions for sorting Long contest on array and string

Course Learning Outcomes (CLOs):

CLO1: Able to improve thinking and reasoning skills in different courses and competitions.

CLO2: Able to operate different data types, conditional logic, and loops and gain the competitive mindset to build problem-solving skills.

CLO3: Able to analyze time and space complexity and optimize code, demonstrate problem-solving skills to different platforms.

CLO4: Competent performing teamwork, interacting with programming solving community, learning strategic planning of problem setting community and style of international standard of problem-solving to adapt the new emerging technologies.

References:

Learning Materials:

Textbooks:

1. The C Programming Language. 2nd Edition Book, Brian Kernighan and Dennis Ritchie

2. Competitive Programmer’s Handbook, Antti Laaksonen

3. Competitive Programming 4: The Lower Bound of Programming Contests, Steven Halim, Felix Halim, Suhendry Effendy

Other Learning Materials: Problem-solving platforms, Webinars, Web Materials, etc.

Course Code: BBA 2211-0414

Course Title: Business Communication

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

This course is designed to give students a comprehensive view of communication, its scope, and importance in business, and the role of communication in establishing a favorable outside-the-firm environment, as well as an effective internal communications program. The various types of business communication media are covered. This course also develops an awareness of the importance of succinct written expression in modern business communication. Many of the assignments are to be keyboarded.

Course Contents:

● Effective Business Communication

● Effective Business Writing

● Delivering your Message

● Writing Preparation

● Understanding your Audience

● Developing Business Presentation

● External Communication

● Presentation to Persuade

● Internal Communication

● Is Silence Killing Your Company?

Course Learning Outcomes:

At the end of the course, the student will be able to –

CLO1: Understand and demonstrate the use of basic and advanced proper writing techniques that today's technology demands, including anticipating audience reaction.

CLO2: Write effective informal and formal reports, and proofread and edit copies of business correspondence.

CLO3: Plan successfully for and participate in meetings and conduct proper techniques in telephone usage as well as use email effectively and efficiently.

CLO4: Use career skills that are needed to succeed, such as using ethical tools, working collaboratively, observing business etiquette, and resolving workplace conflicts.

CLO5: Develop interpersonal skills that contribute to effective and satisfying personal, social and professional relationships, and utilize electronic presentation software.

References:

Learning Materials:

Textbooks:

1. Business Communication for Success - Scott McLean

2. Business Communication Essentials - Courtland L Bovee, Jean A. Scribner, and John Thill

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Business Communication

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

This course is designed to give students a comprehensive view of communication, its scope, and importance in business, and the role of communication in establishing a favorable outside-the-firm environment, as well as an effective internal communications program. The various types of business communication media are covered. This course also develops an awareness of the importance of succinct written expression in modern business communication. Many of the assignments are to be keyboarded.

Course Contents:

● Effective Business Communication

● Effective Business Writing

● Delivering your Message

● Writing Preparation

● Understanding your Audience

● Developing Business Presentation

● External Communication

● Presentation to Persuade

● Internal Communication

● Is Silence Killing Your Company?

Course Learning Outcomes:

At the end of the course, the student will be able to –

CLO1: Understand and demonstrate the use of basic and advanced proper writing techniques that today's technology demands, including anticipating audience reaction.

CLO2: Write effective informal and formal reports, and proofread and edit copies of business correspondence.

CLO3: Plan successfully for and participate in meetings and conduct proper techniques in telephone usage as well as use email effectively and efficiently.

CLO4: Use career skills that are needed to succeed, such as using ethical tools, working collaboratively, observing business etiquette, and resolving workplace conflicts.

CLO5: Develop interpersonal skills that contribute to effective and satisfying personal, social and professional relationships, and utilize electronic presentation software.

References:

Learning Materials:

Textbooks:

1. Business Communication for Success - Scott McLean

2. Business Communication Essentials - Courtland L Bovee, Jean A. Scribner, and John Thill

Other Learning Materials: Journals, Web Materials, etc.

Course Code: MATH 2217-0542

Course Title: Probability & Statistics

Course Type: Theory

Prerequisite: MATH 1213-0541

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

Statistics and probability deal with the study of collecting, analyzing, and presenting data which is essential in taking decisions and making predictions. This course is designed to provide theoretical knowledge regarding data collection and presentation in different techniques, measures of central tendency, dispersion, correlation and regression, sampling, probability, and its distributions.

Course Contents:

1. Fundamentals of statistics:

Definitions of statistics - past and present, Its nature and characteristics, Meaning, Scope, and classification of statistics, Its relation with other disciplines, Limitations, Uses, Misuse, and abuse of statistics; Sources and types of statistical data, etc.

2. Data Collection:

Sampling and Related Issues: Sampling, probability and non-probability sampling, simple random sampling, stratified sampling, cluster sampling, systematic sampling, sampling error, non-sampling error, questionnaire, etc.

3. Organization and Presentation of Data:

Construction of frequency distribution, graphical methods on presentation of data using bar plot, pie chart, histogram, frequency polygon, ogive, stem and leaf plot, box and whisker plot, five number summaries, detection of outliers.

4. Statistical measurements:

Measures of Central Tendency, Measure of dispersion, and their applications.

5. Correlation and Regression:

Introduction, correlation, computation of simple coefficient of correlation, proof of variation of correlation, Scatter diagram, regression, regression lines, simple coefficient of regression, multiple and partial correlations.

6. Basic Concept of Probability:

Concepts of Probability, Sample space, Events, Laws of probability, Conditional probability; Baye’s theorem and its application, Random variables. Discrete and continuous random variables, Probability mass function, Probability density function.

7. Probability distribution:

Distribution function. Joint distribution, Marginal and Conditional distributions, Independence of random variables. Mathematical expectations Chebyshev’s inequality, Discrete and Uniform distribution, Binomial distribution, Poisson distribution, Negative Binomial distribution, Geometric distribution, Hypergeometric distribution, Continuous Uniform distribution, Exponential distribution, Normal distribution, Beta distribution, Gamma distribution, The Central Limit Theorem. Infinite Sequences of Random Variables The Gambler’s Ruin Problem.

Course Learning Outcomes (CLOs):

CLO1: Understand the background, scopes, and basic properties of statistics and probability.

CLO2: Analyze data, data collection, interpreting, and presenting and its probability how likely it will happen.

CLO3: Calculate and interpret statistical measurements, and the probability of any given event from given data.

CLO4: Use statistical knowledge and probability distribution in different practical situations frequently encountered in society, industry, commerce, trade, science, and technology, etc.,

CLO5: Develop statistical models and software for data analysis.

References:

Learning Materials:

Textbooks:

1. Mian M. A .and Mian M. A, Introduction to Statistics, 4th ed, Universal Press, Dhaka

2. Islam M. N. 2006. An Introduction to Statistics and Probability, Book World, Dhaka.

3. Mood, Graybill & Boes, Introduction to the theory of Statistics, 3rd ed. McGraw-Hill.

4. Hogg, R.V. & Craig, A.T. An Introduction to Mathematical Statistics, Mcm.-Colliern, N.Y

5. Sheldon M. Ross, 2007, Introduction to Probability Models, Elsevier, 9th Edition. N.Y.

6. M.K. Roy, 2019, Fundamentals of Probability & Probability Distribution, Romax Pub.s BD

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Probability & Statistics

Course Type: Theory

Prerequisite: MATH 1213-0541

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

Statistics and probability deal with the study of collecting, analyzing, and presenting data which is essential in taking decisions and making predictions. This course is designed to provide theoretical knowledge regarding data collection and presentation in different techniques, measures of central tendency, dispersion, correlation and regression, sampling, probability, and its distributions.

Course Contents:

1. Fundamentals of statistics:

Definitions of statistics - past and present, Its nature and characteristics, Meaning, Scope, and classification of statistics, Its relation with other disciplines, Limitations, Uses, Misuse, and abuse of statistics; Sources and types of statistical data, etc.

2. Data Collection:

Sampling and Related Issues: Sampling, probability and non-probability sampling, simple random sampling, stratified sampling, cluster sampling, systematic sampling, sampling error, non-sampling error, questionnaire, etc.

3. Organization and Presentation of Data:

Construction of frequency distribution, graphical methods on presentation of data using bar plot, pie chart, histogram, frequency polygon, ogive, stem and leaf plot, box and whisker plot, five number summaries, detection of outliers.

4. Statistical measurements:

Measures of Central Tendency, Measure of dispersion, and their applications.

5. Correlation and Regression:

Introduction, correlation, computation of simple coefficient of correlation, proof of variation of correlation, Scatter diagram, regression, regression lines, simple coefficient of regression, multiple and partial correlations.

6. Basic Concept of Probability:

Concepts of Probability, Sample space, Events, Laws of probability, Conditional probability; Baye’s theorem and its application, Random variables. Discrete and continuous random variables, Probability mass function, Probability density function.

7. Probability distribution:

Distribution function. Joint distribution, Marginal and Conditional distributions, Independence of random variables. Mathematical expectations Chebyshev’s inequality, Discrete and Uniform distribution, Binomial distribution, Poisson distribution, Negative Binomial distribution, Geometric distribution, Hypergeometric distribution, Continuous Uniform distribution, Exponential distribution, Normal distribution, Beta distribution, Gamma distribution, The Central Limit Theorem. Infinite Sequences of Random Variables The Gambler’s Ruin Problem.

Course Learning Outcomes (CLOs):

CLO1: Understand the background, scopes, and basic properties of statistics and probability.

CLO2: Analyze data, data collection, interpreting, and presenting and its probability how likely it will happen.

CLO3: Calculate and interpret statistical measurements, and the probability of any given event from given data.

CLO4: Use statistical knowledge and probability distribution in different practical situations frequently encountered in society, industry, commerce, trade, science, and technology, etc.,

CLO5: Develop statistical models and software for data analysis.

References:

Learning Materials:

Textbooks:

1. Mian M. A .and Mian M. A, Introduction to Statistics, 4th ed, Universal Press, Dhaka

2. Islam M. N. 2006. An Introduction to Statistics and Probability, Book World, Dhaka.

3. Mood, Graybill & Boes, Introduction to the theory of Statistics, 3rd ed. McGraw-Hill.

4. Hogg, R.V. & Craig, A.T. An Introduction to Mathematical Statistics, Mcm.-Colliern, N.Y

5. Sheldon M. Ross, 2007, Introduction to Probability Models, Elsevier, 9th Edition. N.Y.

6. M.K. Roy, 2019, Fundamentals of Probability & Probability Distribution, Romax Pub.s BD

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 2215-0613

Course Title: Data Structure and Algorithm

Course Type: Theory

Prerequisite: CSE 1111-0613, CSE 1236-0611

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

This course is intended to enable the students to learn about logical and mathematical models of storing and organizing data using different structural ways of programming methods and techniques. This course is also intended to enable the learners to get a basic idea about algorithmic techniques arising in various practical applications like arrays, sorting and searching, divide and conquer, greedy algorithms, graph traversals, and dynamic programming so that students can analyze and criticize the complexity of the encountered design of existing bench-mark data structure and algorithms and also apply the acquired knowledge to understand advanced algorithm techniques and develop or design efficient algorithms to solve real-world problems.

Course Contents:

1. Introduction: Data Structure and Algorithm Basics, Characteristics, The need for Analysis, Problem Development Steps, Complexity

2. Arrays and Pointer: Single and multi-dimensional arrays, analysis of array insert, delete and search operations both linear and binary search, Pointer

3. Linked Lists: Analysis of insert, remove and search operations in single-linked, doubly-linked, and circular lists

4. Methodology of Analysis: Asymptotic Notation, Best Case, Worst Case, Average Case, Solving Recurrence Equations, Amortized Analysis

5. Asymptotic Analysis: Time Complexity, Space Complexity, Asymptotic Notations, Asymptotic Upper Bound, Asymptotic Lower Bound, Asymptotic Tight Bound, O-Notation, ω- Notation

6. Stack, Queues, and Recursion: Array and linked representations of stacks, comparison of actions on stacks in the two representations, many stacks implemented in an array Prefix, infix, and postfix expressions, utility, and conversion of these expressions from one to another are examples of stack applications. Stacks in recursion: finding recursive solutions to simple problems, recursion advantages, and limits, De-queue, comparison of operations on queues in the two representations, array and linked representations of queues. Applications of Queue.

7. Graph and Trees: Introduction to graphs and trees as data structures; binary trees, binary search trees, analysis of insert, remove, and search operations, recursive and iterative binary search tree traversals. Insert, remove, and search actions on AVL and B trees, as well as height-balanced trees (AVL). Application of Graph and Trees.

8. Heaps: Introduction to heap as a data structure. analysis of insert, extract-min/max, and delete-min/max operations, applications to priority queues.

9. Sorting and Searching (Divide and Conquer): Implementation of sparse matrices, applications of arrays to sorting: selection sort, insertion sort, bubble sort, merge sort, empirical comparison of sorting algorithms

10. Dynamic Programming: Fibonacci number series, Knapsack problem, Tower of Hanoi, All pair shortest path by Floyd-Warshall, Shortest path by Dijkstra

11. Greedy Algorithm: Traveling Salesman Problem, Prim's Minimal Spanning Tree Algorithm, Kruskal's Minimal Spanning Tree Algorithm, Dijkstra's Minimal Spanning Tree Algorithm, Graph-Map Coloring

12. Hash Tables: Introduction to hashing, hash tables, and hashing functions - insertion, collision resolution using open addressing, deletion, searching, and analysis, features of a good hash function.

Course Learning Outcomes (CLOs):

CLO1: Able to express the fundamentals of static and dynamic Data Structure and algorithms and formulate new solutions for problems.

CLO2: Competent to illustrate the design paradigms by identifying problems and analyze the running time and optimize the space complexity.

CLO3: Able to represent the storage mechanism and synthesize efficient algorithms and data structures for complex classic engineering design situations.

CLO4: Competent to handle the operations with rigorous correctness proof and illustrate good programming style and identify the impact of style based on achieved data structure and algorithm knowledge.

References:

Learning Materials;

Textbooks:

1. Data Structures – Edward Martin Reingold; Wilfred J. Hansen (2011)

2. Data structures and algorithm (1st ed) – John E. Hopcroft; Jeffrey D. Ullman (1983)

3. Data structures and algorithm (1st ed) – John E. Hopcroft; Jeffrey D. Ullman(1983)

4. Introduction to Algorithms (3rd ed) - T. H. Cormen; C. E. Leiserson; R. L. Rivest; C. Stein, MIT Press (2009)

5. Algorithm Design (1st ed) - J. Kleinberg; E. Tardos (2005)

6. Algorithm Design and Applications (1st ed) - Michael T. Goodrich; Roberto Tamassia, Wiley (2014)

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Data Structure and Algorithm

Course Type: Theory

Prerequisite: CSE 1111-0613, CSE 1236-0611

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

This course is intended to enable the students to learn about logical and mathematical models of storing and organizing data using different structural ways of programming methods and techniques. This course is also intended to enable the learners to get a basic idea about algorithmic techniques arising in various practical applications like arrays, sorting and searching, divide and conquer, greedy algorithms, graph traversals, and dynamic programming so that students can analyze and criticize the complexity of the encountered design of existing bench-mark data structure and algorithms and also apply the acquired knowledge to understand advanced algorithm techniques and develop or design efficient algorithms to solve real-world problems.

Course Contents:

1. Introduction: Data Structure and Algorithm Basics, Characteristics, The need for Analysis, Problem Development Steps, Complexity

2. Arrays and Pointer: Single and multi-dimensional arrays, analysis of array insert, delete and search operations both linear and binary search, Pointer

3. Linked Lists: Analysis of insert, remove and search operations in single-linked, doubly-linked, and circular lists

4. Methodology of Analysis: Asymptotic Notation, Best Case, Worst Case, Average Case, Solving Recurrence Equations, Amortized Analysis

5. Asymptotic Analysis: Time Complexity, Space Complexity, Asymptotic Notations, Asymptotic Upper Bound, Asymptotic Lower Bound, Asymptotic Tight Bound, O-Notation, ω- Notation

6. Stack, Queues, and Recursion: Array and linked representations of stacks, comparison of actions on stacks in the two representations, many stacks implemented in an array Prefix, infix, and postfix expressions, utility, and conversion of these expressions from one to another are examples of stack applications. Stacks in recursion: finding recursive solutions to simple problems, recursion advantages, and limits, De-queue, comparison of operations on queues in the two representations, array and linked representations of queues. Applications of Queue.

7. Graph and Trees: Introduction to graphs and trees as data structures; binary trees, binary search trees, analysis of insert, remove, and search operations, recursive and iterative binary search tree traversals. Insert, remove, and search actions on AVL and B trees, as well as height-balanced trees (AVL). Application of Graph and Trees.

8. Heaps: Introduction to heap as a data structure. analysis of insert, extract-min/max, and delete-min/max operations, applications to priority queues.

9. Sorting and Searching (Divide and Conquer): Implementation of sparse matrices, applications of arrays to sorting: selection sort, insertion sort, bubble sort, merge sort, empirical comparison of sorting algorithms

10. Dynamic Programming: Fibonacci number series, Knapsack problem, Tower of Hanoi, All pair shortest path by Floyd-Warshall, Shortest path by Dijkstra

11. Greedy Algorithm: Traveling Salesman Problem, Prim's Minimal Spanning Tree Algorithm, Kruskal's Minimal Spanning Tree Algorithm, Dijkstra's Minimal Spanning Tree Algorithm, Graph-Map Coloring

12. Hash Tables: Introduction to hashing, hash tables, and hashing functions - insertion, collision resolution using open addressing, deletion, searching, and analysis, features of a good hash function.

Course Learning Outcomes (CLOs):

CLO1: Able to express the fundamentals of static and dynamic Data Structure and algorithms and formulate new solutions for problems.

CLO2: Competent to illustrate the design paradigms by identifying problems and analyze the running time and optimize the space complexity.

CLO3: Able to represent the storage mechanism and synthesize efficient algorithms and data structures for complex classic engineering design situations.

CLO4: Competent to handle the operations with rigorous correctness proof and illustrate good programming style and identify the impact of style based on achieved data structure and algorithm knowledge.

References:

Learning Materials;

Textbooks:

1. Data Structures – Edward Martin Reingold; Wilfred J. Hansen (2011)

2. Data structures and algorithm (1st ed) – John E. Hopcroft; Jeffrey D. Ullman (1983)

3. Data structures and algorithm (1st ed) – John E. Hopcroft; Jeffrey D. Ullman(1983)

4. Introduction to Algorithms (3rd ed) - T. H. Cormen; C. E. Leiserson; R. L. Rivest; C. Stein, MIT Press (2009)

5. Algorithm Design (1st ed) - J. Kleinberg; E. Tardos (2005)

6. Algorithm Design and Applications (1st ed) - Michael T. Goodrich; Roberto Tamassia, Wiley (2014)

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 2216-0613

Course Title: Data Structures and Algorithm Lab

Course Type: Lab

Prerequisite: Prerequisite: CSE 1111-0613, CSE 1236-0611

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

The main focus of this course is to design and implement basic data structures and algorithms, such as sorting, finding shortest paths, and basic data structures to analyze runtime and memory utilization. Also, this course will help to build programming skills for advanced data structures and algorithm techniques for modern problem solutions.

Laboratory Work:

➢ Write a program to search an element from a list to perform Linear or Binary searching.

➢ Write a program to sort a given number of numerical elements to implement the divide and conquer method using any sorting algorithm like Quick sort, Bubble Sort, Merge Sort, Heap Sort, and other sorting algorithms.

➢ Implement Linked List by using templates. Include functions for insertion, deletion, and search of a number, reverse the list and concatenate two linked lists (include a function and also overload operator +).

➢ Implement a Doubly Linked List using templates. Include functions for insertion, deletion, and search of a number, and reverse the list.

➢ Implement Circular Linked List using templates. Include functions for insertion, deletion, and search of a number, and reverse the list.

➢ Perform Stack operations using Linked List implementation.

➢ Perform Queues operations using Circular Array implementation.

➢ Perform Dynamic Programming using any algorithm 0/1 Knapsack Algorithm

➢ Apply Dynamic Programming knowledge using Dijkstra's Algorithm.

➢ Perform DP Knowledge using Floyd-Warshall Algorithm.

➢ Write a program to calculate factorial and compute the factors of a given no. (i)using recursion, (ii) using iteration

➢ Write a program to display the Fibonacci series (i)using recursion, (ii) using iteration

➢ Write a program to calculate the GCD of 2 numbers (i) with recursion (ii) without recursion

➢ Implement Graph Theory by writing a program using breadth-first search.

➢ Implement Graph Theory by writing a program using depth-first search.

➢ Write a program to reverse the order of the elements in the stack using an additional stack and Queue.

➢ Write a program to implement different Matrix representations using a one-dimensional array.

➢ Write a program to implement various operations on AVL Tree.

➢ Write a program to create a Threaded Binary Tree as per inorder traversal

➢ Apply the Greedy Approach by performing Prim’s and Kruskal’s algorithms.

Course Learning Outcomes (CLOs):

CLO1: Able to identify abstract data structures, implement and empirically analyze linear and non-linear data structures and practice the principles of different data structures and algorithms.

CLO2: Able to design various searching and sorting algorithms and incorporate algorithmic design to create reliable and structured programs.

CLO3: Able to identify the appropriate data structure for a given problem, build practical knowledge to determine and demonstrate bugs in programs and develop software with teamwork in mind.

CLO4: Able to write a program using the optimum data structure or the application at hand and exploit the concept of problem domain analysis and features to improve data structure and algorithm efficiency.

Course Title: Data Structures and Algorithm Lab

Course Type: Lab

Prerequisite: Prerequisite: CSE 1111-0613, CSE 1236-0611

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

The main focus of this course is to design and implement basic data structures and algorithms, such as sorting, finding shortest paths, and basic data structures to analyze runtime and memory utilization. Also, this course will help to build programming skills for advanced data structures and algorithm techniques for modern problem solutions.

Laboratory Work:

➢ Write a program to search an element from a list to perform Linear or Binary searching.

➢ Write a program to sort a given number of numerical elements to implement the divide and conquer method using any sorting algorithm like Quick sort, Bubble Sort, Merge Sort, Heap Sort, and other sorting algorithms.

➢ Implement Linked List by using templates. Include functions for insertion, deletion, and search of a number, reverse the list and concatenate two linked lists (include a function and also overload operator +).

➢ Implement a Doubly Linked List using templates. Include functions for insertion, deletion, and search of a number, and reverse the list.

➢ Implement Circular Linked List using templates. Include functions for insertion, deletion, and search of a number, and reverse the list.

➢ Perform Stack operations using Linked List implementation.

➢ Perform Queues operations using Circular Array implementation.

➢ Perform Dynamic Programming using any algorithm 0/1 Knapsack Algorithm

➢ Apply Dynamic Programming knowledge using Dijkstra's Algorithm.

➢ Perform DP Knowledge using Floyd-Warshall Algorithm.

➢ Write a program to calculate factorial and compute the factors of a given no. (i)using recursion, (ii) using iteration

➢ Write a program to display the Fibonacci series (i)using recursion, (ii) using iteration

➢ Write a program to calculate the GCD of 2 numbers (i) with recursion (ii) without recursion

➢ Implement Graph Theory by writing a program using breadth-first search.

➢ Implement Graph Theory by writing a program using depth-first search.

➢ Write a program to reverse the order of the elements in the stack using an additional stack and Queue.

➢ Write a program to implement different Matrix representations using a one-dimensional array.

➢ Write a program to implement various operations on AVL Tree.

➢ Write a program to create a Threaded Binary Tree as per inorder traversal

➢ Apply the Greedy Approach by performing Prim’s and Kruskal’s algorithms.

Course Learning Outcomes (CLOs):

CLO1: Able to identify abstract data structures, implement and empirically analyze linear and non-linear data structures and practice the principles of different data structures and algorithms.

CLO2: Able to design various searching and sorting algorithms and incorporate algorithmic design to create reliable and structured programs.

CLO3: Able to identify the appropriate data structure for a given problem, build practical knowledge to determine and demonstrate bugs in programs and develop software with teamwork in mind.

CLO4: Able to write a program using the optimum data structure or the application at hand and exploit the concept of problem domain analysis and features to improve data structure and algorithm efficiency.

Course Code: CSE 2234-0613

Course Title: Numerical Methods with MATLAB

Course Type: Criminology

Prerequisite: MATH 1111-0541, CSE 1111-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

This course is an introduction to numerical analysis. The objective of the course is to develop a basic understanding of numerical algorithms and skills to implement algorithms to solve mathematical problems on the computer. Students will learn about the mathematical and computational foundations of numerical approximation and solutions to scientific problems. It covers computer arithmetic, solution of nonlinear equations, interpolation and approximation, numerical integration and differentiation, solution of differential equations, and matrix computation.

Course Contents:

1. Introduction: Basic Numerical Concepts, Approximation and Round off Error, Truncation Errors. Intermediate Value Theorem.

2. Non-linear Equations: Roots of Non-linear Equations, Bracketing Method-Bisection Method, Bracketing Method-false position method, MATLAB Program of Bisection & False Position Method, Open Method-Fixed Point Iteration, Open Method- Newton Raphson Method & Secant Method, MATLAB Program of Newton Raphson and Secant Method.

3. Linear Equation: Naive-Gauss, Gauss Partial Pivoting, Gauss-Jordan Elimination, MATLAB Program of Naive-Gauss ELimination.

Linear Algebraic Equations: Gauss-Seidel iteration Method, MATLAB Program of Gauss-Seidel Elimination.

4. Curve Fitting: Interpolation-Newton’s Divided Difference Formula, MATLAB Program of Interpolation-Newton’s Divided Difference Formula, Regression-Polynomial, Least Square, Linear, and Non-Linear Regression.

5. Numerical Differentiation: High Accuracy, Differentiation Formula, Forward and Backward and Center Difference Formula, MATLAB Program of Numerical Differentiation.

6. Numerical Integration: Trapezoid Rule, Simpson’s Rule, MATLAB Program of Numerical Integration.

Ordinary Differential Equation: Euler’s Method, Runge-Kutta Method.

Course Learning Outcomes (CLOs):

CLO1: Students will be able to understand the basics of numerical concepts with linear/ non-linear/ linear algebra equations.

CLO2: Able to analyze and implement different numerical algorithms.

CLO3: Competent to solve integration, differentiation, and differential equations by numerical methods.

CLO4: Able to solve complex engineering problems using numerical methods and implement them using modern tools like MATLAB.

References:

Learning Materials:

Textbooks:

1. Gerald/Wheatley, Applied Numerical Analysis, Sixth edition

2. Chapra, Numerical Methods for Engineers, Sixth edition

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Numerical Methods with MATLAB

Course Type: Criminology

Prerequisite: MATH 1111-0541, CSE 1111-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

This course is an introduction to numerical analysis. The objective of the course is to develop a basic understanding of numerical algorithms and skills to implement algorithms to solve mathematical problems on the computer. Students will learn about the mathematical and computational foundations of numerical approximation and solutions to scientific problems. It covers computer arithmetic, solution of nonlinear equations, interpolation and approximation, numerical integration and differentiation, solution of differential equations, and matrix computation.

Course Contents:

1. Introduction: Basic Numerical Concepts, Approximation and Round off Error, Truncation Errors. Intermediate Value Theorem.

2. Non-linear Equations: Roots of Non-linear Equations, Bracketing Method-Bisection Method, Bracketing Method-false position method, MATLAB Program of Bisection & False Position Method, Open Method-Fixed Point Iteration, Open Method- Newton Raphson Method & Secant Method, MATLAB Program of Newton Raphson and Secant Method.

3. Linear Equation: Naive-Gauss, Gauss Partial Pivoting, Gauss-Jordan Elimination, MATLAB Program of Naive-Gauss ELimination.

Linear Algebraic Equations: Gauss-Seidel iteration Method, MATLAB Program of Gauss-Seidel Elimination.

4. Curve Fitting: Interpolation-Newton’s Divided Difference Formula, MATLAB Program of Interpolation-Newton’s Divided Difference Formula, Regression-Polynomial, Least Square, Linear, and Non-Linear Regression.

5. Numerical Differentiation: High Accuracy, Differentiation Formula, Forward and Backward and Center Difference Formula, MATLAB Program of Numerical Differentiation.

6. Numerical Integration: Trapezoid Rule, Simpson’s Rule, MATLAB Program of Numerical Integration.

Ordinary Differential Equation: Euler’s Method, Runge-Kutta Method.

Course Learning Outcomes (CLOs):

CLO1: Students will be able to understand the basics of numerical concepts with linear/ non-linear/ linear algebra equations.

CLO2: Able to analyze and implement different numerical algorithms.

CLO3: Competent to solve integration, differentiation, and differential equations by numerical methods.

CLO4: Able to solve complex engineering problems using numerical methods and implement them using modern tools like MATLAB.

References:

Learning Materials:

Textbooks:

1. Gerald/Wheatley, Applied Numerical Analysis, Sixth edition

2. Chapra, Numerical Methods for Engineers, Sixth edition

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 2205-0613

Course Title: Competitive Programming-II

Course Type: Lab

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

This course is for advanced programmers designed to perform well in national and international competitions as well as get themselves certified for the IT industry. The outline focuses on the efficient implementation of Data Structures and algorithms using STL. Also, different problem-solving paradigms as well as set up competitive mindsets among individuals.

Course Contents:

1. Introduction to Competitive Programming: Problem-solving platforms, Tools and libraries, Contest ranking, Career path, Interview overview

2. Introduction to C++: Syntax, Library functions, Input, Output

Warm-up contest

3. Problem-solving paradigm: Implementation, Greedy, Brute force, Data structure and algorithm, string, constructive algorithm, graph, Dynamic programming

4. STL: Standard template libraries, use in previous codes to optimize

5. String in C++: library functions, string with STL

6. Array in C++: array with STL

7. Advanced contest-I

8. Dynamic array: Vector, list, pointer, iterator

9. Set, multiset

10. Stack, Queue

11. Map: Ordered map, unordered_map

12. Advanced contest-II

13. Number theory: Prime number and time complexity optimization, sieve of Eratosthenes, Prime factorization, GCD, LCM

14. Advanced contest-III

15. Recursion

16. Graph Theory: BFS, DFS, problem-solving, 2D grid

17. Tree: Construct tree, tree manipulation, node finding

18. Long advanced contest

Course Learning Outcomes (CLOs):

CLO1: Able to manifest the concept of STL and C++ syntax in real-life problem-solving

CLO2: Able to implement data structure and algorithm in an efficient manner, manipulate and optimize them for different types of problems

CLO3: Able to show their problem-solving skills in national and international platforms and ready for software engineering job position

References:

Learning Materials:

Textbooks:

1. Object Oriented Programming With C++, Balagurusamy

2. Competitive Programmer’s Handbook, Antti Laaksonen

3. Competitive Programming 4: The Lower Bound of Programming Contests, Steven Halim, Felix Halim, Suhendry Effendy

4. Cracking the Coding Interview, Gayle Laakmann McDowell

Other Learning Materials: Problem-solving platforms, webinars, Web Materials, etc.

Course Title: Competitive Programming-II

Course Type: Lab

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

This course is for advanced programmers designed to perform well in national and international competitions as well as get themselves certified for the IT industry. The outline focuses on the efficient implementation of Data Structures and algorithms using STL. Also, different problem-solving paradigms as well as set up competitive mindsets among individuals.

Course Contents:

1. Introduction to Competitive Programming: Problem-solving platforms, Tools and libraries, Contest ranking, Career path, Interview overview

2. Introduction to C++: Syntax, Library functions, Input, Output

Warm-up contest

3. Problem-solving paradigm: Implementation, Greedy, Brute force, Data structure and algorithm, string, constructive algorithm, graph, Dynamic programming

4. STL: Standard template libraries, use in previous codes to optimize

5. String in C++: library functions, string with STL

6. Array in C++: array with STL

7. Advanced contest-I

8. Dynamic array: Vector, list, pointer, iterator

9. Set, multiset

10. Stack, Queue

11. Map: Ordered map, unordered_map

12. Advanced contest-II

13. Number theory: Prime number and time complexity optimization, sieve of Eratosthenes, Prime factorization, GCD, LCM

14. Advanced contest-III

15. Recursion

16. Graph Theory: BFS, DFS, problem-solving, 2D grid

17. Tree: Construct tree, tree manipulation, node finding

18. Long advanced contest

Course Learning Outcomes (CLOs):

CLO1: Able to manifest the concept of STL and C++ syntax in real-life problem-solving

CLO2: Able to implement data structure and algorithm in an efficient manner, manipulate and optimize them for different types of problems

CLO3: Able to show their problem-solving skills in national and international platforms and ready for software engineering job position

References:

Learning Materials:

Textbooks:

1. Object Oriented Programming With C++, Balagurusamy

2. Competitive Programmer’s Handbook, Antti Laaksonen

3. Competitive Programming 4: The Lower Bound of Programming Contests, Steven Halim, Felix Halim, Suhendry Effendy

4. Cracking the Coding Interview, Gayle Laakmann McDowell

Other Learning Materials: Problem-solving platforms, webinars, Web Materials, etc.

Course Code: CSE 3151-0714

Course Title: Digital Logic Design

Course Type: Theory

Prerequisite: EEE 1211-0714

Credits: 3

Contact Hours: 42

Year/Level: 2

Semester/Term: 2

Rationale:

To empower the learner to design digital circuits and logic gates, inspect the basic knowledge of digital electronics, perceive knowledge about different types of integrated circuits and gates and develop a substantial background for advanced digital electronic courses and signals and sequences of a digital circuit through numbers.

Course Contents:

1. Number systems: Representation of numbers in different bases, Addition, and subtraction in different bases, Complement: Subtraction using complements, Binary multiplication & division.

2. Binary codes: Different coding systems, Boolean algebra, various gates, Sum of products and product of sums, Standard and canonical forms, and other logical operations.

3. Simplification of Boolean functions: Karnaugh map method, Tabular method of simplification; Implementation of the logic circuit using various gates, Universal gates.

4. Combinational logic circuit: Design procedure: Adder, Subtractor, Code converters, Parity bit checker and magnitude comparator, Analysis of different combinational circuits, Encoder, decoder, Multiplexer, Demultiplexer, ROM, PLA, and their applications.

5. Flip-flops: SR, JK, Master-slave, T, and D type flip-flops and their characteristic tables & equations; Triggering of flip-flops, Flipflop, Excitation table.

6. Sequential circuits: Introduction to sequential circuits, Analysis and synthesis of synchronous and asynchronous sequential circuits.

7. Counters: Classifications, Synchronous and asynchronous counter design and analysis, Ring counter, Johnson counters, Ripple counter and counter with the parallel load.

8. Registers: Classification, Shift registers, Circular registers and their applications and registers with the parallel load. Basic Concept of Application Specific IC (ASIC) design.

9. Digital IC logic families: Brief description of TTL, DTL, RTL, ECL, I2L, MOS, and CMOS logic and their characteristics, principles of operation, and application.

10. Memory Units: Various memory devices and their interfacing. Converters: Digital to Analog (D/A), Analog to Digital (A/D) converters, and their applications.

Course Learning Outcomes (CLOs);

CLO1: Able to learn the fundamental concepts of digital logic design, number systems, basic and universal gates, and design combinational and sequential logic circuits with state machines.

CLO2: Competent to demonstrate the acquired knowledge by solving different problems related to the design and analysis of digital electronic circuits including Binary Coded Decimal, Boolean and switching algebra, and multi-variable Karnaugh map methods.

CLO3: Able to identify and diagnose the small-scale combinational circuits: arithmetic logic units, adder, subtractor, encoders, decoders, multiplexers, de-multiplexers

CLO4: Competent to design digital electronic and logic circuits using digital integrated circuits.

References:

Learning Materials;[

Textbooks:

1. Digital Logic and Computer Design (4th Edition) - M. Morris Mano (2007)

2. Digital Computer Electronics (3rd Edition) - Albert P. Malvino, Jerald A Brown (2001)

3. Modern Digital Electronics by R.P. Jain

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Digital Logic Design

Course Type: Theory

Prerequisite: EEE 1211-0714

Credits: 3

Contact Hours: 42

Year/Level: 2

Semester/Term: 2

Rationale:

To empower the learner to design digital circuits and logic gates, inspect the basic knowledge of digital electronics, perceive knowledge about different types of integrated circuits and gates and develop a substantial background for advanced digital electronic courses and signals and sequences of a digital circuit through numbers.

Course Contents:

1. Number systems: Representation of numbers in different bases, Addition, and subtraction in different bases, Complement: Subtraction using complements, Binary multiplication & division.

2. Binary codes: Different coding systems, Boolean algebra, various gates, Sum of products and product of sums, Standard and canonical forms, and other logical operations.

3. Simplification of Boolean functions: Karnaugh map method, Tabular method of simplification; Implementation of the logic circuit using various gates, Universal gates.

4. Combinational logic circuit: Design procedure: Adder, Subtractor, Code converters, Parity bit checker and magnitude comparator, Analysis of different combinational circuits, Encoder, decoder, Multiplexer, Demultiplexer, ROM, PLA, and their applications.

5. Flip-flops: SR, JK, Master-slave, T, and D type flip-flops and their characteristic tables & equations; Triggering of flip-flops, Flipflop, Excitation table.

6. Sequential circuits: Introduction to sequential circuits, Analysis and synthesis of synchronous and asynchronous sequential circuits.

7. Counters: Classifications, Synchronous and asynchronous counter design and analysis, Ring counter, Johnson counters, Ripple counter and counter with the parallel load.

8. Registers: Classification, Shift registers, Circular registers and their applications and registers with the parallel load. Basic Concept of Application Specific IC (ASIC) design.

9. Digital IC logic families: Brief description of TTL, DTL, RTL, ECL, I2L, MOS, and CMOS logic and their characteristics, principles of operation, and application.

10. Memory Units: Various memory devices and their interfacing. Converters: Digital to Analog (D/A), Analog to Digital (A/D) converters, and their applications.

Course Learning Outcomes (CLOs);

CLO1: Able to learn the fundamental concepts of digital logic design, number systems, basic and universal gates, and design combinational and sequential logic circuits with state machines.

CLO2: Competent to demonstrate the acquired knowledge by solving different problems related to the design and analysis of digital electronic circuits including Binary Coded Decimal, Boolean and switching algebra, and multi-variable Karnaugh map methods.

CLO3: Able to identify and diagnose the small-scale combinational circuits: arithmetic logic units, adder, subtractor, encoders, decoders, multiplexers, de-multiplexers

CLO4: Competent to design digital electronic and logic circuits using digital integrated circuits.

References:

Learning Materials;[

Textbooks:

1. Digital Logic and Computer Design (4th Edition) - M. Morris Mano (2007)

2. Digital Computer Electronics (3rd Edition) - Albert P. Malvino, Jerald A Brown (2001)

3. Modern Digital Electronics by R.P. Jain

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 3152-0714

Course Title: Digital Logic Design Lab

Course Type: Lab

Prerequisite: EEE 1212-0714

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

The major focus of this course is to provide knowledge of problem-solving skills with digital logic circuits and to empower the learner to inspect and perceive the basic building blocks of combinational and sequential circuits so that students can design the modern digital circuit and understand the operations of hardware models.

Lab Tasks:

➢ Identification and verification of the truth tables of digital logic gates.

➢ Simplification and Realization of Boolean Algebraic Function

➢ Design and implementation using Universal Gates.

➢ Introduction to Combinational circuit and simplification of Karnaugh Map (K-Map)

➢ Construction of Adder, Subtractor, and Magnitude Operator using basic gates.

➢ Design and Simplification of Boolean Function using Logisim.

➢ Design and Circuit construction of Combinational Circuit using Multiplexers and Demultiplexers.

➢ Design and Circuit construction of a Combinational Circuit using a Decoder/Encoder

➢ Introduction to Sequential Circuit using Basic Flip-Flop.

➢ Design and simplification of Synchronous and Asynchronous ICs

Course Learning Outcomes (CLOs):

CLO1: Able to demonstrate the fundamental logic designing tools using combinational and sequential circuits.

CLO2: Able to interpret practical knowledge to design different Boolean and Switching algebra and simple digital circuits.

CLO3: Able to design, apply and simplify logic functions with different integrated circuits and components.

CLO4: Competent to synthesize simple real-life projects and correlate them with the given problem.

Course Title: Digital Logic Design Lab

Course Type: Lab

Prerequisite: EEE 1212-0714

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

The major focus of this course is to provide knowledge of problem-solving skills with digital logic circuits and to empower the learner to inspect and perceive the basic building blocks of combinational and sequential circuits so that students can design the modern digital circuit and understand the operations of hardware models.

Lab Tasks:

➢ Identification and verification of the truth tables of digital logic gates.

➢ Simplification and Realization of Boolean Algebraic Function

➢ Design and implementation using Universal Gates.

➢ Introduction to Combinational circuit and simplification of Karnaugh Map (K-Map)

➢ Construction of Adder, Subtractor, and Magnitude Operator using basic gates.

➢ Design and Simplification of Boolean Function using Logisim.

➢ Design and Circuit construction of Combinational Circuit using Multiplexers and Demultiplexers.

➢ Design and Circuit construction of a Combinational Circuit using a Decoder/Encoder

➢ Introduction to Sequential Circuit using Basic Flip-Flop.

➢ Design and simplification of Synchronous and Asynchronous ICs

Course Learning Outcomes (CLOs):

CLO1: Able to demonstrate the fundamental logic designing tools using combinational and sequential circuits.

CLO2: Able to interpret practical knowledge to design different Boolean and Switching algebra and simple digital circuits.

CLO3: Able to design, apply and simplify logic functions with different integrated circuits and components.

CLO4: Competent to synthesize simple real-life projects and correlate them with the given problem.

Course Code: CSE 3143-0611

Course Title: Theory of Computing

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

Intended to learn the basic techniques to solve problems efficiently on a model of computation, computational process, their limits and the elementary ways in which a computer works.

Course Contents:

1. Overview: Introduction to TOC, Different Layers of TOC, Finite State Machine, Context Free Grammar, Turing Machine, Undecidable

2. Finite State Machine: Introduction to FSM, Deterministic Finite Automata, Non-Deterministic Finite Automata, Formal Definition, Regular Language, Conversion of NFA to DFA, Minimization of DFA, Epsilon NFA, Conversion of Epsilon NFA to NFA

3. Regular Expression: Construction of Mealy Machine, Construction of Moore Machine, Conversion of Moore Machine to Mealy Machine, Conversion of Mealy Machine to Moore Machine, Examples and Identities of Regular Expression, Arden’s Theorem, Example proof using identities, Designing RE, NFA to RE, DFA to RE, Equivalence of Two Finite Automata

4. Regular & Context Free Grammar: Introduction to Regular Grammar, Derivation from Grammar, Regular Language and Finite Automata Problem Solving, Derivation Tree, Ambiguous Grammar, Simplification of CFG, Chomsky Normal Form, Greibach Normal Form, Pumping Lemma, Push Down Automata

5. Turing Machine: Introduction to Turing Machine, Turing Machine Problem Solving, Turing Machine Programming Techniques, Non-Deterministic Turing Machine, Decidability, Universal Turing Machine

6. Conclusion of TOC: Decidability and Undecidability, The Halting Problem, Undecidability of Halting Problem, The Post Correspondence Problem

Course Learning Outcomes (CLOs):

CLO1: Able to identify and evaluate the mathematical foundation of Finite Automata and Regular Expression including automata theory.

CLO2: Able to synthesize the foundation of formal languages, grammar, decidability, and complexity as a model of computation.

CLO3: Ability to correlate and assess context-free grammar and push down automata.

CLO4: Able to analyze and manipulate Turing machines and undecidability as a model of real-world computation.

CLO5: Able to analyze complexity theory to enhance the ability to conduct mathematical proofs for computation.

References:

Learning Materials:

Textbooks:

1. Michael Sipser, Introduction to Theory of Computation, Published by Thomson, 2nd Edition.

2. John C. Martin, Introduction to Languages and Theory of Computation, Published by McGraw-Hill, 3rd Edition.

3. Elements of the Theory of Computation (2nd Edition) – H.R. Lewis; C.H. Papadimitriou (1997)

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Theory of Computing

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

Intended to learn the basic techniques to solve problems efficiently on a model of computation, computational process, their limits and the elementary ways in which a computer works.

Course Contents:

1. Overview: Introduction to TOC, Different Layers of TOC, Finite State Machine, Context Free Grammar, Turing Machine, Undecidable

2. Finite State Machine: Introduction to FSM, Deterministic Finite Automata, Non-Deterministic Finite Automata, Formal Definition, Regular Language, Conversion of NFA to DFA, Minimization of DFA, Epsilon NFA, Conversion of Epsilon NFA to NFA

3. Regular Expression: Construction of Mealy Machine, Construction of Moore Machine, Conversion of Moore Machine to Mealy Machine, Conversion of Mealy Machine to Moore Machine, Examples and Identities of Regular Expression, Arden’s Theorem, Example proof using identities, Designing RE, NFA to RE, DFA to RE, Equivalence of Two Finite Automata

4. Regular & Context Free Grammar: Introduction to Regular Grammar, Derivation from Grammar, Regular Language and Finite Automata Problem Solving, Derivation Tree, Ambiguous Grammar, Simplification of CFG, Chomsky Normal Form, Greibach Normal Form, Pumping Lemma, Push Down Automata

5. Turing Machine: Introduction to Turing Machine, Turing Machine Problem Solving, Turing Machine Programming Techniques, Non-Deterministic Turing Machine, Decidability, Universal Turing Machine

6. Conclusion of TOC: Decidability and Undecidability, The Halting Problem, Undecidability of Halting Problem, The Post Correspondence Problem

Course Learning Outcomes (CLOs):

CLO1: Able to identify and evaluate the mathematical foundation of Finite Automata and Regular Expression including automata theory.

CLO2: Able to synthesize the foundation of formal languages, grammar, decidability, and complexity as a model of computation.

CLO3: Ability to correlate and assess context-free grammar and push down automata.

CLO4: Able to analyze and manipulate Turing machines and undecidability as a model of real-world computation.

CLO5: Able to analyze complexity theory to enhance the ability to conduct mathematical proofs for computation.

References:

Learning Materials:

Textbooks:

1. Michael Sipser, Introduction to Theory of Computation, Published by Thomson, 2nd Edition.

2. John C. Martin, Introduction to Languages and Theory of Computation, Published by McGraw-Hill, 3rd Edition.

3. Elements of the Theory of Computation (2nd Edition) – H.R. Lewis; C.H. Papadimitriou (1997)

Other Learning Materials: Journals, Web Materials, etc.

Course Code: HRM 1103 - 0413

Course Title: Principles of Management

Course Type: Theory

Prerequisite: None

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1st

Semester/Term: 1

Rationale:

This course provides the knowledge of introductory management to apply management concepts successfully and often involves focusing more on skills development and the human side of the organization.

Course Contents:

1. Concept of Management: Definition of Management, management theories, management functions, management skills, management levels, and the role of managers.

2. Management and environment: internal environment, external environment, and how management aligns with those environmental aspects in terms of sustainable development.

3. Planning: Define planning, planning process, types of plans, levels of planning, and aligning planning with strategy.

4. Organizing: Define organizing, explain organizational chart and structure, organizational design, types of organizations, define staffing, define work groups and teams.

5. Motivation: Define motivation and motivational theories.

6. Leading: Define leading and leadership theories.

7. Controlling: Define controlling, types of controlling, and controlling processes.

Course Learning Outcomes (CLOs):

Upon successful completion of the requirements for this course, students will be:

CLO1: able to understand the basic knowledge of management.

CLO2: able to describe the planning concept and its processes.

CLO3: able to illustrate organizational aspects in different types of organizational settings.

CLO4: able to understand motivational concepts.

CLO5: able to understand how to lead an organization.

CLO6: able to explain the controlling processes in an organizational setting.

References:

Learning Materials:

Textbooks:

1. Fundamentals of Management (2016) by Ricky W. Griffin.

2. Management (2006) by Robert Kreitner.

3. Management (1988) by Heinz Weihrich and Harold Koontz

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Principles of Management

Course Type: Theory

Prerequisite: None

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 1st

Semester/Term: 1

Rationale:

This course provides the knowledge of introductory management to apply management concepts successfully and often involves focusing more on skills development and the human side of the organization.

Course Contents:

1. Concept of Management: Definition of Management, management theories, management functions, management skills, management levels, and the role of managers.

2. Management and environment: internal environment, external environment, and how management aligns with those environmental aspects in terms of sustainable development.

3. Planning: Define planning, planning process, types of plans, levels of planning, and aligning planning with strategy.

4. Organizing: Define organizing, explain organizational chart and structure, organizational design, types of organizations, define staffing, define work groups and teams.

5. Motivation: Define motivation and motivational theories.

6. Leading: Define leading and leadership theories.

7. Controlling: Define controlling, types of controlling, and controlling processes.

Course Learning Outcomes (CLOs):

Upon successful completion of the requirements for this course, students will be:

CLO1: able to understand the basic knowledge of management.

CLO2: able to describe the planning concept and its processes.

CLO3: able to illustrate organizational aspects in different types of organizational settings.

CLO4: able to understand motivational concepts.

CLO5: able to understand how to lead an organization.

CLO6: able to explain the controlling processes in an organizational setting.

References:

Learning Materials:

Textbooks:

1. Fundamentals of Management (2016) by Ricky W. Griffin.

2. Management (2006) by Robert Kreitner.

3. Management (1988) by Heinz Weihrich and Harold Koontz

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: GED 3113

Course Title: Principles of Management

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hour: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

It is essential for professionals in any field to have an understanding of the ethical problems and principles in their field. But anyone, no matter what their job, must deal with many other professions as well. Part of the Principles of Management is the understanding of the ethics of other professions: how they interact and what can be expected from them as correct ethical behavior. In turn, any professional will benefit from critical scrutiny of their own ethics by those from other professions.

The general principles of Management will be examined, as well as the distinctive problems of the different fields. The course is taught each, covering the ethics of several major professions: Engineering Ethics, Legal Ethics, and Research Ethics. Topics covered will also include the nature of a profession, professional codes of ethics, confidentiality, whistle-blowing, and the responsibility of engineers to the environment and society.

Course Contents:

Definition and scopes of ethics. Different branches of ethics. Social change and the emergence of new technologies. History and development of Engineering Ethics. Science and Technology necessity and application. Study of Ethics in Engineering. Applied Ethics in engineering. Human qualities of an engineer. The obligation of an engineer to the clients. The attitude of an engineer towards other engineers. Measures are to be taken in order to improve the quality of the engineering profession. Ethical Expectations: Employers and Employees; inter-professional relationship: Professional Organization- maintaining a commitment to Ethical standards. Desired characteristics of a professional code. Institutionalization of Ethical conduct.

Course Learning Outcomes (CLOs):

CLO1: Would be able to understand the concepts of ethics, the scope of ethics and different branches of ethics, social change, the emergence of ethics, history, and the development of engineering ethics.

CLO2: Would be able to apply ethics in daily life and all the activities of regular work.

CLO3: Would be able to build an ethical standard and high commitment towards jobs.

CLO4: Would be able to develop the human qualities of the engineers.

CLO5: Would be able to implement ethical behaviors in inter-professional relationships within the organization and outside of the organization.

Course Title: Principles of Management

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hour: 42

Total Marks: 100

Year/Level: 1

Semester/Term: 1

Rationale:

It is essential for professionals in any field to have an understanding of the ethical problems and principles in their field. But anyone, no matter what their job, must deal with many other professions as well. Part of the Principles of Management is the understanding of the ethics of other professions: how they interact and what can be expected from them as correct ethical behavior. In turn, any professional will benefit from critical scrutiny of their own ethics by those from other professions.

The general principles of Management will be examined, as well as the distinctive problems of the different fields. The course is taught each, covering the ethics of several major professions: Engineering Ethics, Legal Ethics, and Research Ethics. Topics covered will also include the nature of a profession, professional codes of ethics, confidentiality, whistle-blowing, and the responsibility of engineers to the environment and society.

Course Contents:

Definition and scopes of ethics. Different branches of ethics. Social change and the emergence of new technologies. History and development of Engineering Ethics. Science and Technology necessity and application. Study of Ethics in Engineering. Applied Ethics in engineering. Human qualities of an engineer. The obligation of an engineer to the clients. The attitude of an engineer towards other engineers. Measures are to be taken in order to improve the quality of the engineering profession. Ethical Expectations: Employers and Employees; inter-professional relationship: Professional Organization- maintaining a commitment to Ethical standards. Desired characteristics of a professional code. Institutionalization of Ethical conduct.

Course Learning Outcomes (CLOs):

CLO1: Would be able to understand the concepts of ethics, the scope of ethics and different branches of ethics, social change, the emergence of ethics, history, and the development of engineering ethics.

CLO2: Would be able to apply ethics in daily life and all the activities of regular work.

CLO3: Would be able to build an ethical standard and high commitment towards jobs.

CLO4: Would be able to develop the human qualities of the engineers.

CLO5: Would be able to implement ethical behaviors in inter-professional relationships within the organization and outside of the organization.

Course Code: GED 3115-0411

Course Title: Principle of Accounting

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

Principles of Accounting course is included in the syllabus so that the students can be skilled at the accounting equation, Conceptual framework of accounting, completing the process of the accounting cycle, & Ethics in Accounting because if the students are not skilled of the above contents, they will not be able to understand calculations of business operations, to trace the loopholes of accounting procedural calculations and take decisions efficiently and independently.

Course Contents:

1. The Nature and Environment of Accounting: Definition, Need to Study Accounting, Employment Opportunities in Accounting, Accounting and Bookkeeping, Users of Accounting Information and their Decision, The Environment and The Development of Accounting Standards, Conceptual Framework Study, Generally Accepted Accounting Principles (GAAP). Basic Environmental Assumptions and Principles, Standard Setting Body (FASB, IASB, IFRS, and BAS, etc.), Nature of Financial Statements, Accounting Equation, and Ethics in Accounting.

2. The Double Entry Recording System: Accounting Cycle, Transactions- The Accounts, Chart of Accounts, Debit, Credit, Determine the Balance of an account, Normal Balance of an Account, The Journal- Journalizing, Special Journals, Posting, Cross Indexing, Compound Entries, The Ledger, and Preparation of Trial Balance.

3. Preparation of Worksheet: Basis of Accounting, Recording of Adjusting Entries. Correcting Entries, Closing Entries, Post Closing Trial balance, Reversing Entries, and Worksheet for Preparing Financial Statements.

4. Financial Statements for Merchandise Operations: Merchandising Activities, Procedures for Accounting for Inventories, Preparing Financial Statements, Income Statement: Single Step, Multiple Step, Statement of Retained Earnings, Classified Balance Sheet, Usefulness of the Balance Sheet, and Limitations of Balance Sheet.

5. Special Journals: Definition, Classes of Special Journal, Effects of Special Journal on General Journal.

Course Learning Outcomes (CLOs):

CLO1: Able to use the accounting equation to recognize the valid causes of the changes of equity in the daily life of financial areas

CLO2: Able to use the conceptual framework of accounting to understand logical operations of financial activities

CLO3: Able to complete the processes of the accounting cycle to prepare financial statements

CLO4: Able to analyze the procedure of business operations to investigate and analyze various business problems

CLO5: Able to understand and analyze the information communicated through the Financial Statements to take decisions independently

CLO6: Able to trace the loopholes of accounting procedural calculations based on ethics in accounting so that there will be no chance of being duped and false presentation

References:

Learning Materials:

Text Books:

1. Accounting Principles by Kieso, D. E & Weygantt, E. I.

2. Financial Accounting by Jerry J. Weygandt & Paul D. Kimmel

3. Intermediate Accounting by Loren A, Nikolai et. Al

4. Accounting: A Business Perspective by Roger H. Harmenson et al

5. Fundamental Accounting Principles by John Wild & Ken W. Shaw & Barbara Chiappetta.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Principle of Accounting

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 1

Rationale:

Principles of Accounting course is included in the syllabus so that the students can be skilled at the accounting equation, Conceptual framework of accounting, completing the process of the accounting cycle, & Ethics in Accounting because if the students are not skilled of the above contents, they will not be able to understand calculations of business operations, to trace the loopholes of accounting procedural calculations and take decisions efficiently and independently.

Course Contents:

1. The Nature and Environment of Accounting: Definition, Need to Study Accounting, Employment Opportunities in Accounting, Accounting and Bookkeeping, Users of Accounting Information and their Decision, The Environment and The Development of Accounting Standards, Conceptual Framework Study, Generally Accepted Accounting Principles (GAAP). Basic Environmental Assumptions and Principles, Standard Setting Body (FASB, IASB, IFRS, and BAS, etc.), Nature of Financial Statements, Accounting Equation, and Ethics in Accounting.

2. The Double Entry Recording System: Accounting Cycle, Transactions- The Accounts, Chart of Accounts, Debit, Credit, Determine the Balance of an account, Normal Balance of an Account, The Journal- Journalizing, Special Journals, Posting, Cross Indexing, Compound Entries, The Ledger, and Preparation of Trial Balance.

3. Preparation of Worksheet: Basis of Accounting, Recording of Adjusting Entries. Correcting Entries, Closing Entries, Post Closing Trial balance, Reversing Entries, and Worksheet for Preparing Financial Statements.

4. Financial Statements for Merchandise Operations: Merchandising Activities, Procedures for Accounting for Inventories, Preparing Financial Statements, Income Statement: Single Step, Multiple Step, Statement of Retained Earnings, Classified Balance Sheet, Usefulness of the Balance Sheet, and Limitations of Balance Sheet.

5. Special Journals: Definition, Classes of Special Journal, Effects of Special Journal on General Journal.

Course Learning Outcomes (CLOs):

CLO1: Able to use the accounting equation to recognize the valid causes of the changes of equity in the daily life of financial areas

CLO2: Able to use the conceptual framework of accounting to understand logical operations of financial activities

CLO3: Able to complete the processes of the accounting cycle to prepare financial statements

CLO4: Able to analyze the procedure of business operations to investigate and analyze various business problems

CLO5: Able to understand and analyze the information communicated through the Financial Statements to take decisions independently

CLO6: Able to trace the loopholes of accounting procedural calculations based on ethics in accounting so that there will be no chance of being duped and false presentation

References:

Learning Materials:

Text Books:

1. Accounting Principles by Kieso, D. E & Weygantt, E. I.

2. Financial Accounting by Jerry J. Weygandt & Paul D. Kimmel

3. Intermediate Accounting by Loren A, Nikolai et. Al

4. Accounting: A Business Perspective by Roger H. Harmenson et al

5. Fundamental Accounting Principles by John Wild & Ken W. Shaw & Barbara Chiappetta.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 3131-0612

Course Title: Data Communication and Networking

Course Type: Theory

Prerequisite: N/A

Credits:3

Contact Hours:42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

To produce effective gadget communication, each virtual device, and its design must be precise. It is vital to comprehend the system's structure, divisions, equipment, and procedures. This course focuses on data communications and designing and administering local area networks (LANs). Its goals include learning about computer network organization and execution and acquiring a theoretical understanding of computer networks. Students will learn about the Open Systems Interconnection (OSI) communication model, network topology, essential signaling, transmission concepts, error detection, correction, recovery, multi-layer LAN, MAN, WAN designs, bridges, routers, gateways, network naming and addressing, and local and remote processes. Students should be able to get a complete understanding of a conventional computer network after completing the course.

Course Contents:

1. Introduction to Computer Networks: IP address, VLSM, application, transport, and data link layer protocols, Vlan-VTP, IPv6, and NAT.

2. Fundamentals of signals and data communication: Network Topology, Digital modulation: ASK, FSK, Multiple access techniques: TDM, FDM.

3. Protocol hierarchies: Demonstration of the OSI model's fundamental concepts and description of the characteristics of various layers.

4. Computer network components, protocols, and latest technologies: Hubs, Bridges, and Switches, Fast Ethernet; (Acquire an understanding of computer network components, protocols, and latest technologies, as well as their applications.)

5. Application layer services: Web, HTTP, FTP, SMTP, DNS architecture (This course also covers the application layer protocol HTTP (used by the World Wide Web) and web-based programming, computer networks' layered design, and critical ideas from the application layer to the link layer.)

6. Introduction to transport layer: UDP, TCP; Principles of Reliable data transfer, Principles of congestion control, TCP, Congestion control;

7. Introduction to Network and Data Link Layer: Network layer protocols and routing, Multiple access protocol: Standards IEEE 802.*, IPV4, IPV6, ARP, RARP, IP address and IP subnetting, Data link control, Link layer and services, Error detection and Correction

8. Network security: Cryptography, DES, public key algorithm, Authentication, Digital signatures.

Course Learning Outcomes (CLOs):

CLO1: Comprehend the principles of data communications and networking and the purpose of the OSI and TCP/IP network layering models and able to explain how layered approaches are used to organize computer networks

CLO2: Able to identify computer networking technological trends and Describe how Internet packets are delivered

CLO3: Based on the layer idea, will be able to evaluate the contents of a provided data link layer packet and With the help of a given address block, create logical sub-address blocks

CLO4: Able to identify how noise, attenuation, and distortion affect the signal transmission, as well as analog and digital data encoding methods and digital transmission.

CLO5: Acknowledge how to use local area network (LAN) components such as bridges, switches, routers, backbone networks, IP addressing, and subnetting.

References:

Learning Materials:

Textbooks:

1. Forouzan, B. A., Coombs, C. A., & Fegan, S. C. (2001). Data communications and networking. Boston: McGraw-Hill.

2. William Stallings, Data and Computer Communications, Published by Pearson, 8th Edition.

3. James Kurose and Keith Ross, Computer Networking: A Top-Down Approach, Published by Addison-Wesley, 6th Edition.

4. Andrew S. Tanenbaum and David J. Wetheral, Computer Networks, Published by Prentice Hall, 5th Edition.

Other Learning Materials: Journals and Web Materials, etc.

Course Title: Data Communication and Networking

Course Type: Theory

Prerequisite: N/A

Credits:3

Contact Hours:42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

To produce effective gadget communication, each virtual device, and its design must be precise. It is vital to comprehend the system's structure, divisions, equipment, and procedures. This course focuses on data communications and designing and administering local area networks (LANs). Its goals include learning about computer network organization and execution and acquiring a theoretical understanding of computer networks. Students will learn about the Open Systems Interconnection (OSI) communication model, network topology, essential signaling, transmission concepts, error detection, correction, recovery, multi-layer LAN, MAN, WAN designs, bridges, routers, gateways, network naming and addressing, and local and remote processes. Students should be able to get a complete understanding of a conventional computer network after completing the course.

Course Contents:

1. Introduction to Computer Networks: IP address, VLSM, application, transport, and data link layer protocols, Vlan-VTP, IPv6, and NAT.

2. Fundamentals of signals and data communication: Network Topology, Digital modulation: ASK, FSK, Multiple access techniques: TDM, FDM.

3. Protocol hierarchies: Demonstration of the OSI model's fundamental concepts and description of the characteristics of various layers.

4. Computer network components, protocols, and latest technologies: Hubs, Bridges, and Switches, Fast Ethernet; (Acquire an understanding of computer network components, protocols, and latest technologies, as well as their applications.)

5. Application layer services: Web, HTTP, FTP, SMTP, DNS architecture (This course also covers the application layer protocol HTTP (used by the World Wide Web) and web-based programming, computer networks' layered design, and critical ideas from the application layer to the link layer.)

6. Introduction to transport layer: UDP, TCP; Principles of Reliable data transfer, Principles of congestion control, TCP, Congestion control;

7. Introduction to Network and Data Link Layer: Network layer protocols and routing, Multiple access protocol: Standards IEEE 802.*, IPV4, IPV6, ARP, RARP, IP address and IP subnetting, Data link control, Link layer and services, Error detection and Correction

8. Network security: Cryptography, DES, public key algorithm, Authentication, Digital signatures.

Course Learning Outcomes (CLOs):

CLO1: Comprehend the principles of data communications and networking and the purpose of the OSI and TCP/IP network layering models and able to explain how layered approaches are used to organize computer networks

CLO2: Able to identify computer networking technological trends and Describe how Internet packets are delivered

CLO3: Based on the layer idea, will be able to evaluate the contents of a provided data link layer packet and With the help of a given address block, create logical sub-address blocks

CLO4: Able to identify how noise, attenuation, and distortion affect the signal transmission, as well as analog and digital data encoding methods and digital transmission.

CLO5: Acknowledge how to use local area network (LAN) components such as bridges, switches, routers, backbone networks, IP addressing, and subnetting.

References:

Learning Materials:

Textbooks:

1. Forouzan, B. A., Coombs, C. A., & Fegan, S. C. (2001). Data communications and networking. Boston: McGraw-Hill.

2. William Stallings, Data and Computer Communications, Published by Pearson, 8th Edition.

3. James Kurose and Keith Ross, Computer Networking: A Top-Down Approach, Published by Addison-Wesley, 6th Edition.

4. Andrew S. Tanenbaum and David J. Wetheral, Computer Networks, Published by Prentice Hall, 5th Edition.

Other Learning Materials: Journals and Web Materials, etc.

Course Code: CSE 3132-0612

Course Title: Data Communication and Networking Lab

Course Type: Lab

Prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

Students learn how to create and operate a computer communication network and acquire expertise with modern LAN systems' installation, monitoring, and troubleshooting. Students should be able to build, construct, and manage a conventional computer network after completing the course.

Lab Tasks:

➢ In-depth study of network devices, performing the Installation and Configuration of the Network components.

➢ Getting Started with the Cisco packet tracer.

➢ Using network tools such as a network simulator, set up TCP/IP Protocol on the Personal Computer Network (Cisco Packet tracer).

➢ Examine the layout and syntax of TCP/IP layer protocols.

➢ Connect the devices to a Local Area Network (LAN) and learn how to use basic network commands and network setup instructions.

➢ Network topology configuration with packet tracer software.

➢ Implement Static Routing on a network.

➢ Configure Dynamic Routing.

➢ Configure the Distance Vector Routing Protocols, also known as RIP and IGRP.

➢ Configurations of Administration Fundamentals for Switch.

➢ Configure and design a small Network using a router like TPLink.

➢ Configure Wireless MAC Filtering Routers.

➢ Construct a computer network project using the Cisco packet tracer simulator.

Course Learning Outcomes (CLOs):

CLO1: Be familiar with the Cisco packet tracer simulation tool and will be able to use hubs, bridges, and switches to create a simple LAN.

CLO2: Able to do the routing protocol configuration and implementation.

CLO3: Able to examine the obstacles to network construction and potential solutions.

Course Title: Data Communication and Networking Lab

Course Type: Lab

Prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale:

Students learn how to create and operate a computer communication network and acquire expertise with modern LAN systems' installation, monitoring, and troubleshooting. Students should be able to build, construct, and manage a conventional computer network after completing the course.

Lab Tasks:

➢ In-depth study of network devices, performing the Installation and Configuration of the Network components.

➢ Getting Started with the Cisco packet tracer.

➢ Using network tools such as a network simulator, set up TCP/IP Protocol on the Personal Computer Network (Cisco Packet tracer).

➢ Examine the layout and syntax of TCP/IP layer protocols.

➢ Connect the devices to a Local Area Network (LAN) and learn how to use basic network commands and network setup instructions.

➢ Network topology configuration with packet tracer software.

➢ Implement Static Routing on a network.

➢ Configure Dynamic Routing.

➢ Configure the Distance Vector Routing Protocols, also known as RIP and IGRP.

➢ Configurations of Administration Fundamentals for Switch.

➢ Configure and design a small Network using a router like TPLink.

➢ Configure Wireless MAC Filtering Routers.

➢ Construct a computer network project using the Cisco packet tracer simulator.

Course Learning Outcomes (CLOs):

CLO1: Be familiar with the Cisco packet tracer simulation tool and will be able to use hubs, bridges, and switches to create a simple LAN.

CLO2: Able to do the routing protocol configuration and implementation.

CLO3: Able to examine the obstacles to network construction and potential solutions.

Course Code: CSE 3108-0613

Course Title: Integrated Design Project I

Type: Lab

Prerequisite: CSE 2121-0613, CSE 1214-0613

Credits: 2

Contact Hours: 28

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

The major focus of this course is the elicitation of requirements from top-level stakeholders and making necessary documentation. Moreover, culminates demonstration of skills and knowledge achieved to solve real-life problems.

Course Outlines:

⮚ Able to select a suitable project topic

⮚ Submit project proposal comparing different candidate system

⮚ Perform literature study

⮚ Perform requirement analysis

⮚ Prepare system requirement specification document

⮚ Able to develop a tentative methodology

Course Learning Outcomes (CLOs):

CLO1: Able to develop systems’ requirement specifications for top-level customer requirements

CLO2: Able to analyze, investigate and compare design alternative subsystems and select a suitable candidate system

CLO3: Able to develop a design concept and elaborate it through to a detailed design by decomposing a system concept into component subsystems and identifying its standards.

References:

Learning Materials:

Textbooks:

1. Project Management, 4th edition, Stephen hartley

2. Software Requirements & Specifications, by Michael J. Jackson and Michael Jackson

Other Learning Materials: Problem-solving platforms, webinars, Web Materials

Course Title: Integrated Design Project I

Type: Lab

Prerequisite: CSE 2121-0613, CSE 1214-0613

Credits: 2

Contact Hours: 28

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

The major focus of this course is the elicitation of requirements from top-level stakeholders and making necessary documentation. Moreover, culminates demonstration of skills and knowledge achieved to solve real-life problems.

Course Outlines:

⮚ Able to select a suitable project topic

⮚ Submit project proposal comparing different candidate system

⮚ Perform literature study

⮚ Perform requirement analysis

⮚ Prepare system requirement specification document

⮚ Able to develop a tentative methodology

Course Learning Outcomes (CLOs):

CLO1: Able to develop systems’ requirement specifications for top-level customer requirements

CLO2: Able to analyze, investigate and compare design alternative subsystems and select a suitable candidate system

CLO3: Able to develop a design concept and elaborate it through to a detailed design by decomposing a system concept into component subsystems and identifying its standards.

References:

Learning Materials:

Textbooks:

1. Project Management, 4th edition, Stephen hartley

2. Software Requirements & Specifications, by Michael J. Jackson and Michael Jackson

Other Learning Materials: Problem-solving platforms, webinars, Web Materials

Course Code: CSE 3219-0613

Course Title: Compiler Construction

Course Type: Theory

prerequisite: CSE 1111-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

The rationale of the Course:

This course is intended to enable the students to understand and apply the fundamental techniques and practical features of the construction of a compiler and translation process that underlie the practice of various phases of compiler construction.

Course Contents:

1. Introduction to Compiler: Interpreter and Compiler, Typical Implementations, Hybrid Approaches, Brief introduction of the phases of the compiler, Why study compilers.

2. Lexical Analysis: Token, Lexical Error, Manage Input Buffer, Kleene Closure, Regular Expression, Regular Language, Finite State Automata, Thomson’s Construction, Hopcroft’s Algorithm, Partitioning.

3. Parser: LL and LR parser, Error Handling, Error Recovery Strategies, Context Free Grammar, Derivation, Ambiguous Grammar, Predictive Parsing, Left Recursion Elimination, First & Follow, Pre-Computed Parsing Table, Test Driven Parsing Algorithm, Bottom-up Parsing, Handle, Shift-Reduce Parsing, LR(0) items, SLR, LALR., CLR

4. Intermediate Code Generator: Three address codes, Quadruples, Triple, Indirect Triple, Translating Expressions, Synthesized code, and place attributes.

5. Code Optimization: Basic blocks and control flow graphs, Transformation on a basic block, Structure preserving transformation, Algebraic Transformation, Loops, Loop Optimization, Array Indexing, Common subexpression elimination

6. Code Generation and Register Allocation: Register allocation, issues, web-based regular allocation, convex sets and live ranges, Interference, Graph Coloring, Splitting, Register Targeting

Course Learning Outcomes (CLOs):

CLO1: Able to identify the architecture, function, purpose, and components of a compiler in programming languages.

CLO2: Able to separate the phases of the compiler to understand language translation and specify the structure of advanced language features.

CLO3: Able to analyze the runtime environments, memory organization, and various parsing techniques in the compilation process.

CLO4: Able to apply software tools and techniques for lifelong learning durability of compiler construction phases.

References:

Learning Materials:

Textbooks:

1. Compiler: Principles, Techniques & Tools (2nd ed)- Alfred V Aho, Monica SLam, Ravi Sethi, and Jeffrey D Ullman, Pearson/Addison Wesley (2006).

2. Engineering A Compiler (2nd Ed) - Linda Torczon and Keith Cooper, Morgan Kaufmann Publishers Inc (2011).

3. Compiler Construction, Theory, and Design by Willam A. Barette

4. Compiler Design Theory by Philip

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Compiler Construction

Course Type: Theory

prerequisite: CSE 1111-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 2

Semester/Term: 2

The rationale of the Course:

This course is intended to enable the students to understand and apply the fundamental techniques and practical features of the construction of a compiler and translation process that underlie the practice of various phases of compiler construction.

Course Contents:

1. Introduction to Compiler: Interpreter and Compiler, Typical Implementations, Hybrid Approaches, Brief introduction of the phases of the compiler, Why study compilers.

2. Lexical Analysis: Token, Lexical Error, Manage Input Buffer, Kleene Closure, Regular Expression, Regular Language, Finite State Automata, Thomson’s Construction, Hopcroft’s Algorithm, Partitioning.

3. Parser: LL and LR parser, Error Handling, Error Recovery Strategies, Context Free Grammar, Derivation, Ambiguous Grammar, Predictive Parsing, Left Recursion Elimination, First & Follow, Pre-Computed Parsing Table, Test Driven Parsing Algorithm, Bottom-up Parsing, Handle, Shift-Reduce Parsing, LR(0) items, SLR, LALR., CLR

4. Intermediate Code Generator: Three address codes, Quadruples, Triple, Indirect Triple, Translating Expressions, Synthesized code, and place attributes.

5. Code Optimization: Basic blocks and control flow graphs, Transformation on a basic block, Structure preserving transformation, Algebraic Transformation, Loops, Loop Optimization, Array Indexing, Common subexpression elimination

6. Code Generation and Register Allocation: Register allocation, issues, web-based regular allocation, convex sets and live ranges, Interference, Graph Coloring, Splitting, Register Targeting

Course Learning Outcomes (CLOs):

CLO1: Able to identify the architecture, function, purpose, and components of a compiler in programming languages.

CLO2: Able to separate the phases of the compiler to understand language translation and specify the structure of advanced language features.

CLO3: Able to analyze the runtime environments, memory organization, and various parsing techniques in the compilation process.

CLO4: Able to apply software tools and techniques for lifelong learning durability of compiler construction phases.

References:

Learning Materials:

Textbooks:

1. Compiler: Principles, Techniques & Tools (2nd ed)- Alfred V Aho, Monica SLam, Ravi Sethi, and Jeffrey D Ullman, Pearson/Addison Wesley (2006).

2. Engineering A Compiler (2nd Ed) - Linda Torczon and Keith Cooper, Morgan Kaufmann Publishers Inc (2011).

3. Compiler Construction, Theory, and Design by Willam A. Barette

4. Compiler Design Theory by Philip

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 3220-0613

Course Title: Compiler Construction Lab

Course Type: Lab

prerequisite: 1112-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale;

The main focus of this course is to learn and implement different phases, and tokenizers and to be able to write the code using Python Programming language to understand the construction of a Compiler.

Lab Tasks:

➢ Design a lexical analyzer for a given language and the lexical analyzer should ignore redundant spaces, tabs, and newlines.

➢ Write a program to identify whether a given line is a comment or not.

➢ Write a program to test whether a given identifier is valid or not.

➢ Write a program to simulate a lexical analyzer for validating operators

➢ Write a program to simulate a lexical analyzer for validating operators.

➢ Write a program for constructing LL (1) parsing.

➢ Write a program for constructing recursive descent parsing.

➢ Write a program to recognize strings under 'a', 'a*b+', 'abb'.

➢ Write a program to implement LALR parsing.

➢ Write a program to implement operator precedence parsing

➢ Write a program to implement Program semantic rules to calculate the expression that takes an expression with digits, + and * and computes the value

➢ Write a program to generate machine code from an abstract syntax tree generated by the parser. The instruction set specified in Note 2 may be considered the target code.

Course Learning Outcomes (CLOs):

CLO1: Able to identify and implement the working principles of computer systems and their working components to build, assess and analyze the software and hardware aspects of it.

CLO2: Able to utilize basic techniques and stuff to perform syntax-directed translation of a high-level programming language into an executable code.

CLO3: Ability to employ modern computer languages, environments, and platforms to apply standard practices and strategies in software project development.

Course Title: Compiler Construction Lab

Course Type: Lab

prerequisite: 1112-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 2

Semester/Term: 2

Rationale;

The main focus of this course is to learn and implement different phases, and tokenizers and to be able to write the code using Python Programming language to understand the construction of a Compiler.

Lab Tasks:

➢ Design a lexical analyzer for a given language and the lexical analyzer should ignore redundant spaces, tabs, and newlines.

➢ Write a program to identify whether a given line is a comment or not.

➢ Write a program to test whether a given identifier is valid or not.

➢ Write a program to simulate a lexical analyzer for validating operators

➢ Write a program to simulate a lexical analyzer for validating operators.

➢ Write a program for constructing LL (1) parsing.

➢ Write a program for constructing recursive descent parsing.

➢ Write a program to recognize strings under 'a', 'a*b+', 'abb'.

➢ Write a program to implement LALR parsing.

➢ Write a program to implement operator precedence parsing

➢ Write a program to implement Program semantic rules to calculate the expression that takes an expression with digits, + and * and computes the value

➢ Write a program to generate machine code from an abstract syntax tree generated by the parser. The instruction set specified in Note 2 may be considered the target code.

Course Learning Outcomes (CLOs):

CLO1: Able to identify and implement the working principles of computer systems and their working components to build, assess and analyze the software and hardware aspects of it.

CLO2: Able to utilize basic techniques and stuff to perform syntax-directed translation of a high-level programming language into an executable code.

CLO3: Ability to employ modern computer languages, environments, and platforms to apply standard practices and strategies in software project development.

Course Code: CSE 3223-0612

Course Title: Database Management System

Course Type: Theory

prerequisite: CSE 1214-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

A database management system (DBMS) is an important component of modern information systems. Database applications are ubiquitous, ranging in size from small in-memory databases to terabytes and even across different application domains. This course focuses on the basics of knowledge bases and relational database management systems, as well as current developments in database theory and practice.

Course Contents:

1. Introduction to Basic Database Concepts: The Course Outline and Objective, Database Definition, Importance of Databases, Shortcomings of Traditional File Processing Systems, Levels of Data, Different Types of Database Users, History of DBMSs, Advantages, and Disadvantages of DBMSs.

2. Database Architecture: Three Level Schema Architecture, Data Independence, Database Languages Database, Data Model and DBMS, Functions, and Components of a DBMS Multi-user DBMS Architecture.

3. Database Planning, Design, and Administration: The Information System Life Cycle, DBS Development Life Cycle, DB Planning System Definition, Requirements Collection, and Analysis, DB Design, DBMS Selection Application Design, Prototyping, Implementation, Data Conversion, and Loading Testing, Operational Maintenance, CASE Tools, Data Administration and Database Administration.

4. Fact-Finding Techniques: What facts are collected, Techniques, A worked example

5. Entity-Relationship Modeling: Semantic Data Models, Introduction to Entity-Relationship Data Model Different Constructs of E-R Data Model, Abstraction Process Modeling different types of Entities and Attributes. Cardinality and Degree of a Relationship, Unary, Binary and n-array Relationships.

6. Entity-Relationship Modeling Case Studies

7. Relational Model and Languages: Introduction to Relational Data Model, Brief History Advantages, Relational Model Terminology, Mathematical Relations, Database Relations Characteristics of Relations, Understanding tables, The Concept of Key, Different Types of Keys, Integrity Constraints Over Relations, Key Constraints, Foreign Key Constraints General Constraints, Data dictionaries, Views.

8. Normalization: Objectives, Functional Dependency, Inference Rules, First Normal Form, Full Functional Dependency, Second Normal Form, Transitive Dependency, Third Normal Form, Boyce-Codd Normal Form.

9. Data Manipulation Languages: Relational Algebra: Unary and Binary operations, Selection, Projection, Cartesian Product Different types of Joins, Union, Intersection, Division.

10. Relational Algebra Practice

11. SQL Queries: Insert, Delete, Select, Update, Where, Order by

12. SQL Queries with Joins: Types of joins, Sub queries

13. Indexing: Types of SQL indexing

14. Presentation of projects

Course Learning Outcomes (CLOs):

CLO1: Able to apply analytical skills to create conceptual designs for real problems and create database documents such as data standards, procedures, and data dictionary definitions.

CLO2: To be able to draw a relational database model using the Entity Relationship (ER) model to explain the basic elements of a database management system.

CLO3: Would be able to evaluate the logical design and transform it into a specific data model to meet the storage needs of your system.

CLO4: Able to evaluate the capabilities of MSSQL / MySQL / Oracle-related products to maintain the integrity and performance of your enterprise database.

References Books:

Learning Materials:

Textbooks:

1. Database System Concepts, Abraham Silberschartz, Henry F. Korth and S Sudershan, Published by McGraw-Hill, 7th Edition.

2. Database Systems: Design, Implementation, and Management, by Carlos Coronel & Steven Morris & Peter Rob

3. Beginning Oracle SQL for Oracle Database 12c, 3rd edition,

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Database Management System

Course Type: Theory

prerequisite: CSE 1214-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

A database management system (DBMS) is an important component of modern information systems. Database applications are ubiquitous, ranging in size from small in-memory databases to terabytes and even across different application domains. This course focuses on the basics of knowledge bases and relational database management systems, as well as current developments in database theory and practice.

Course Contents:

1. Introduction to Basic Database Concepts: The Course Outline and Objective, Database Definition, Importance of Databases, Shortcomings of Traditional File Processing Systems, Levels of Data, Different Types of Database Users, History of DBMSs, Advantages, and Disadvantages of DBMSs.

2. Database Architecture: Three Level Schema Architecture, Data Independence, Database Languages Database, Data Model and DBMS, Functions, and Components of a DBMS Multi-user DBMS Architecture.

3. Database Planning, Design, and Administration: The Information System Life Cycle, DBS Development Life Cycle, DB Planning System Definition, Requirements Collection, and Analysis, DB Design, DBMS Selection Application Design, Prototyping, Implementation, Data Conversion, and Loading Testing, Operational Maintenance, CASE Tools, Data Administration and Database Administration.

4. Fact-Finding Techniques: What facts are collected, Techniques, A worked example

5. Entity-Relationship Modeling: Semantic Data Models, Introduction to Entity-Relationship Data Model Different Constructs of E-R Data Model, Abstraction Process Modeling different types of Entities and Attributes. Cardinality and Degree of a Relationship, Unary, Binary and n-array Relationships.

6. Entity-Relationship Modeling Case Studies

7. Relational Model and Languages: Introduction to Relational Data Model, Brief History Advantages, Relational Model Terminology, Mathematical Relations, Database Relations Characteristics of Relations, Understanding tables, The Concept of Key, Different Types of Keys, Integrity Constraints Over Relations, Key Constraints, Foreign Key Constraints General Constraints, Data dictionaries, Views.

8. Normalization: Objectives, Functional Dependency, Inference Rules, First Normal Form, Full Functional Dependency, Second Normal Form, Transitive Dependency, Third Normal Form, Boyce-Codd Normal Form.

9. Data Manipulation Languages: Relational Algebra: Unary and Binary operations, Selection, Projection, Cartesian Product Different types of Joins, Union, Intersection, Division.

10. Relational Algebra Practice

11. SQL Queries: Insert, Delete, Select, Update, Where, Order by

12. SQL Queries with Joins: Types of joins, Sub queries

13. Indexing: Types of SQL indexing

14. Presentation of projects

Course Learning Outcomes (CLOs):

CLO1: Able to apply analytical skills to create conceptual designs for real problems and create database documents such as data standards, procedures, and data dictionary definitions.

CLO2: To be able to draw a relational database model using the Entity Relationship (ER) model to explain the basic elements of a database management system.

CLO3: Would be able to evaluate the logical design and transform it into a specific data model to meet the storage needs of your system.

CLO4: Able to evaluate the capabilities of MSSQL / MySQL / Oracle-related products to maintain the integrity and performance of your enterprise database.

References Books:

Learning Materials:

Textbooks:

1. Database System Concepts, Abraham Silberschartz, Henry F. Korth and S Sudershan, Published by McGraw-Hill, 7th Edition.

2. Database Systems: Design, Implementation, and Management, by Carlos Coronel & Steven Morris & Peter Rob

3. Beginning Oracle SQL for Oracle Database 12c, 3rd edition,

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 3224-0612

Course Title: Database Management System Lab

Course Type: Lab

prerequisite: CSE 1112-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

This course is aimed to explain basic database principles, teach how to build databases, and provide hands-on experience by creating a real-world e-commerce database application as part of a term project. Also, to get an understanding of database architecture, from conceptual design through the implementation of database schemas and user interfaces.

Lab Tasks:

➢ Draw an E-R diagram and convert entities and relationships to a relation table for a given scenario- Two assignments shall be carried out i.e. consider two different scenarios (eg. bank, college)

➢ Write relational algebra queries for a given set of relations.

➢ Perform the following- Viewing all databases, Creating a Database, Viewing all Tables in a Database, Creating Tables (With and Without Constraints), Inserting/Updating/Deleting Records in a Table, Saving (Commit) and Undoing (rollback)

➢ Perform the following- Altering a Table, Dropping/Truncating/Renaming Tables, and Backing up / Restoring a Database.

➢ For a given set of relation schemes, create tables and perform the following-

➢ Simple Queries, Simple Queries with Aggregate functions, Queries with Aggregate functions (group by and having clause), Queries involving- Date Functions, String Functions, Math Functions

➢ Join Queries- Inner Join, Outer Join

➢ Subqueries- With IN clause, With EXISTS clause

➢ For a given set of related tables perform the following- Creating Views (with and without check option), Dropping views, Selecting from a view

➢ Write a Pl/SQL program using FOR loop to insert ten rows into a database table.

➢ Given the table EMPLOYEE (EmpNo, Name, Salary, Designation, DeptID), write a cursor to select the five highest-paid employees from the table.

➢ Illustrate how you can embed PL/SQL in a high-level host language such as C/Java And demonstrates how a banking debit transaction might be done.

➢ Given an integer i, write a PL/SQL procedure to insert the tuple (i, 'xxx') into a given relation.

Course Learning Outcomes (CLOs):

CLO1: Able to apply the basic concepts of Database Systems and Applications.

CLO2: Able to use the basics of SQL and construct queries using SQL in database creation and interaction.

CLO3: Able to design a commercial relational database system (Oracle, MySQL) by writing SQL using the system.

CLO4: Able to analyze and Select storage and recovery techniques of database systems.

Course Title: Database Management System Lab

Course Type: Lab

prerequisite: CSE 1112-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

This course is aimed to explain basic database principles, teach how to build databases, and provide hands-on experience by creating a real-world e-commerce database application as part of a term project. Also, to get an understanding of database architecture, from conceptual design through the implementation of database schemas and user interfaces.

Lab Tasks:

➢ Draw an E-R diagram and convert entities and relationships to a relation table for a given scenario- Two assignments shall be carried out i.e. consider two different scenarios (eg. bank, college)

➢ Write relational algebra queries for a given set of relations.

➢ Perform the following- Viewing all databases, Creating a Database, Viewing all Tables in a Database, Creating Tables (With and Without Constraints), Inserting/Updating/Deleting Records in a Table, Saving (Commit) and Undoing (rollback)

➢ Perform the following- Altering a Table, Dropping/Truncating/Renaming Tables, and Backing up / Restoring a Database.

➢ For a given set of relation schemes, create tables and perform the following-

➢ Simple Queries, Simple Queries with Aggregate functions, Queries with Aggregate functions (group by and having clause), Queries involving- Date Functions, String Functions, Math Functions

➢ Join Queries- Inner Join, Outer Join

➢ Subqueries- With IN clause, With EXISTS clause

➢ For a given set of related tables perform the following- Creating Views (with and without check option), Dropping views, Selecting from a view

➢ Write a Pl/SQL program using FOR loop to insert ten rows into a database table.

➢ Given the table EMPLOYEE (EmpNo, Name, Salary, Designation, DeptID), write a cursor to select the five highest-paid employees from the table.

➢ Illustrate how you can embed PL/SQL in a high-level host language such as C/Java And demonstrates how a banking debit transaction might be done.

➢ Given an integer i, write a PL/SQL procedure to insert the tuple (i, 'xxx') into a given relation.

Course Learning Outcomes (CLOs):

CLO1: Able to apply the basic concepts of Database Systems and Applications.

CLO2: Able to use the basics of SQL and construct queries using SQL in database creation and interaction.

CLO3: Able to design a commercial relational database system (Oracle, MySQL) by writing SQL using the system.

CLO4: Able to analyze and Select storage and recovery techniques of database systems.

Course Code: CSE 3253-0714

Course Title: Microprocessor and Assembly Language

Course Type: Theory

prerequisite: CSE 3151

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

Microprocessor and interfacing include the architecture, interfacing, and logical operations of the Intel 8086 microprocessors. This course is for students who already have good knowledge of computer architecture and are familiar with computer hardware. Students will gain fundamental knowledge about microprocessors, their features, and operational mechanisms from this course.

Course Contents:

1. Introduction to the microprocessor: Basic concept of microprocessor, history, usage.

2. Microprocessor-based microcomputer: Introduction to microcomputer, microcomputer vs microprocessor, major components of the microprocessor, and the basic operation of the microcomputer.

3. Features of Microprocessor: Microprocessors of Intel Family, Microprocessor Basic Features, Pin Diagram of Various Microprocessors.

4. Input/Output: Introduction to I/O devices, I/O ports, Programmed I/O, Standard I/O, Memory driven I/O, Direct Memory Access

5. 8086 Introduction: 8086 Introduction, Functional Blocks, 8086 Pin Diagram, 8086 Internal Basic Architecture

6. 8086 Architecture: 8086 Detailed Architecture(BIU, EU)

7. 8086 Operations: 8086 Function of Execution Unit, Registers, Pin Operations

8. 8086 Interfacing: 8086 & Memory Interfacing, Memory Organization, RAM Operation, DRAM, SRAM, Memory Decoding, Address Mapping

9. 8086 Interrupt: Basic interrupt, Hardware Interrupt, Interrupt Vector Table, Interrupt Vector

10. Communication Protocol: Serial Communication, Parallel Communication, Terminology, Advantages and Disadvantages.

11. SAP -1: SAP-1 Architecture, SAP-1 Exercise, SAP Routines

12. Analog Digital: Analog to Digital, Digital to Analog Convention, Analog and Digital Sensors, Pulse Code Modulation

13. 8086 Bus timing: General BUS Operation, Machine Cycles, Ready Pin and Wait States

14. 8086 Pipelining: Trivia, Pipeline Introduction, Fetch and Execution Cycle of 8086 Processor.

15. Memory Management Techniques: Fragmentation, Differences Between Internal and External Fragmentation.

16. Protected Mode: Limitation of Real Mode operation, Importance of Memory Management Unit, Virtual Memory Management by MMU

Course Learning Outcomes (CLOs):

CLO1: Learn the fundamentals of Microprocessor based computer systems.

CLO2: Competent to identify a detailed hardware structure of the Microprocessor.

CLO3: Competent to analyze the logical operation of microprocessors and realize the Engineering problems which are solved by the usage of microprocessors.

References:

Learning Materials:

Textbooks:

1. Md. Rafiquzzaman, Microprocessor and Microcomputer Based System Design, Published by CRC Press, 2nd Edition.

2. Douglas Hall, Microprocessors and Interfacing Programming and Hardware, Published by McGraw Hill, 3rd Edition.

3. Robert L. Hummel, PC Magazine Programmer’s Technical Reference: The Processor and Coprocessor, Published by Ziff-Davis Press, Illustrated Edition.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Microprocessor and Assembly Language

Course Type: Theory

prerequisite: CSE 3151

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

Microprocessor and interfacing include the architecture, interfacing, and logical operations of the Intel 8086 microprocessors. This course is for students who already have good knowledge of computer architecture and are familiar with computer hardware. Students will gain fundamental knowledge about microprocessors, their features, and operational mechanisms from this course.

Course Contents:

1. Introduction to the microprocessor: Basic concept of microprocessor, history, usage.

2. Microprocessor-based microcomputer: Introduction to microcomputer, microcomputer vs microprocessor, major components of the microprocessor, and the basic operation of the microcomputer.

3. Features of Microprocessor: Microprocessors of Intel Family, Microprocessor Basic Features, Pin Diagram of Various Microprocessors.

4. Input/Output: Introduction to I/O devices, I/O ports, Programmed I/O, Standard I/O, Memory driven I/O, Direct Memory Access

5. 8086 Introduction: 8086 Introduction, Functional Blocks, 8086 Pin Diagram, 8086 Internal Basic Architecture

6. 8086 Architecture: 8086 Detailed Architecture(BIU, EU)

7. 8086 Operations: 8086 Function of Execution Unit, Registers, Pin Operations

8. 8086 Interfacing: 8086 & Memory Interfacing, Memory Organization, RAM Operation, DRAM, SRAM, Memory Decoding, Address Mapping

9. 8086 Interrupt: Basic interrupt, Hardware Interrupt, Interrupt Vector Table, Interrupt Vector

10. Communication Protocol: Serial Communication, Parallel Communication, Terminology, Advantages and Disadvantages.

11. SAP -1: SAP-1 Architecture, SAP-1 Exercise, SAP Routines

12. Analog Digital: Analog to Digital, Digital to Analog Convention, Analog and Digital Sensors, Pulse Code Modulation

13. 8086 Bus timing: General BUS Operation, Machine Cycles, Ready Pin and Wait States

14. 8086 Pipelining: Trivia, Pipeline Introduction, Fetch and Execution Cycle of 8086 Processor.

15. Memory Management Techniques: Fragmentation, Differences Between Internal and External Fragmentation.

16. Protected Mode: Limitation of Real Mode operation, Importance of Memory Management Unit, Virtual Memory Management by MMU

Course Learning Outcomes (CLOs):

CLO1: Learn the fundamentals of Microprocessor based computer systems.

CLO2: Competent to identify a detailed hardware structure of the Microprocessor.

CLO3: Competent to analyze the logical operation of microprocessors and realize the Engineering problems which are solved by the usage of microprocessors.

References:

Learning Materials:

Textbooks:

1. Md. Rafiquzzaman, Microprocessor and Microcomputer Based System Design, Published by CRC Press, 2nd Edition.

2. Douglas Hall, Microprocessors and Interfacing Programming and Hardware, Published by McGraw Hill, 3rd Edition.

3. Robert L. Hummel, PC Magazine Programmer’s Technical Reference: The Processor and Coprocessor, Published by Ziff-Davis Press, Illustrated Edition.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 3254-0714

Course Title: Microprocessor and Assembly Language Lab

Course Type: Lab

prerequisite: CSE 3152

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

This course prepares the students with sufficient knowledge about microprocessors and assembly language. A compiler translates high or mid-level languages to assembly language to perform microprocessor-level computation. Students will learn about the 8086 microprocessor, EMU8086, and basic codes to perform specific tasks on microprocessors.

Lab Tasks:

➢ Introduction: 8086 microprocessors, registers, pointers, flags, and setting up EMU8086

➢ Working with Flow control, conditional and unconditional jumps using EMU8086

➢ Create loop, shift, and rotate using EMU8086

➢ Programming with flow control and nested loop

➢ Solve basic problems with loop, shift, rotate, flow contents, and nested loops.

➢ Programming with flow control and nested loop part-2 and procedures

➢ Programming with Procedures part-2 and Stack

➢ Problem-solving using Stack and Procedures

➢ Create Multiplication and division, INDEC, OUT DEC using EMU8086

➢ Working with array operations

➢ Working with string operations

➢ Problem-solving with array and string on EMU8086

➢ Working with Interrupt

➢ Conduct code using recursion

➢ Final overview and solve basic coding problems using EMU8086

Course Learning Outcomes (CLOs):

CLO1: Learn to program with 8086 assembly language with EMU8086.

CLO2: Analyze the basic procedures of mid-level language to assembly language translation and optimization.

CLO3: Competent to understand basic concepts of I/O devices, Arrays, Stacks, Addressing, Interrupts, and Strings for solving complex problems

References:

Learning Materials:

Textbooks:

1. PC Ytha Yu and Charles Marut, Assembly language Programming and Programming Organization of the IBM

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Microprocessor and Assembly Language Lab

Course Type: Lab

prerequisite: CSE 3152

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 1

Rationale:

This course prepares the students with sufficient knowledge about microprocessors and assembly language. A compiler translates high or mid-level languages to assembly language to perform microprocessor-level computation. Students will learn about the 8086 microprocessor, EMU8086, and basic codes to perform specific tasks on microprocessors.

Lab Tasks:

➢ Introduction: 8086 microprocessors, registers, pointers, flags, and setting up EMU8086

➢ Working with Flow control, conditional and unconditional jumps using EMU8086

➢ Create loop, shift, and rotate using EMU8086

➢ Programming with flow control and nested loop

➢ Solve basic problems with loop, shift, rotate, flow contents, and nested loops.

➢ Programming with flow control and nested loop part-2 and procedures

➢ Programming with Procedures part-2 and Stack

➢ Problem-solving using Stack and Procedures

➢ Create Multiplication and division, INDEC, OUT DEC using EMU8086

➢ Working with array operations

➢ Working with string operations

➢ Problem-solving with array and string on EMU8086

➢ Working with Interrupt

➢ Conduct code using recursion

➢ Final overview and solve basic coding problems using EMU8086

Course Learning Outcomes (CLOs):

CLO1: Learn to program with 8086 assembly language with EMU8086.

CLO2: Analyze the basic procedures of mid-level language to assembly language translation and optimization.

CLO3: Competent to understand basic concepts of I/O devices, Arrays, Stacks, Addressing, Interrupts, and Strings for solving complex problems

References:

Learning Materials:

Textbooks:

1. PC Ytha Yu and Charles Marut, Assembly language Programming and Programming Organization of the IBM

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 3246-0613

Course Title: Web Programming

Course Type: Theory Prerequisite: CSE 2121-0613, CSE 3223, CSE 1214-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

This course covers the tools and technology for developing web applications, the HTTP protocol, dynamic web programming, web application optimization, and security improvements, preparing you to become a full-stack web application developer.

Course Contents:

Web Servers, web browsers

HTML Introduction

HTML Syntax

HTML Head, Title

HTML Attributes, Headings, Paragraphs

HTML Links, Images

HTML Comments, Styles, Color, Tables

HTML Forms & their design etc.

Create web pages purely with HTML code.

CSS Introduction

PHP/JSP Introduction

PHP Syntax

PHP Variable, Echo, Data Types

PHP String, Constant, Operators

PHP If-Else, Switch, While, For Loops

PHP Form Handling & Validation

Connecting the website with the server using PHP

Retrieving, Inserting, Deleting, or Updating data using PHP

JavaScript Introduction

JavaScript Syntax

JavaScript Basics Variables, Operators, Arithmetic, etc

Different frameworks

Project Integration

Laboratory work / Experiments:

➢ Introduction to web servers and web browsers and mark-up language (HTML).

➢ Create web pages purely with HTML code.

➢ Create a web page to show applications of CSS files.

➢ Create a web page to show the application of form controls and design using Bootstrap

➢ Form validation and file handling in PHP/JSP/ASP.NET.

➢ PHP/JSP user management system

➢ Design a sample database

➢ Practice data definition language and data manipulation language

➢ Experiment with database connection and session and cookies in PHP/JSP/ASP.NET

➢ Study of JavaScript and applying JavaScript to web pages

➢ Create a web page with HTML, CSS, JavaScript & PHP/JSP/ASP.NET

➢ Study with the framework: LARAVEL/JSP/JSOUP/.NET

➢ Working on the team project with bitbucket and preparing a demo

➢ Working on the team project with bitbucket

** Bitbucket is a Git-based source code repository hosting service owned by Atlassian. Bitbucket offers both commercial plans and free accounts with an unlimited number of private repositories.

Course Learning Outcomes (CLOs):

CLO1: Demonstrate and comprehend the fundamentals of web programming.

CLO2: Using HTML and CSS code, create well-structured, readily maintainable, standards-compliant web pages.

CLO3: Add dynamic content to pages that match unique requirements and interests with JavaScript.

CLO4: To make dynamic pages, and form validation mechanisms, use the JavaScript frameworks jQuery and AngularJS and ensure client-side web security.

References:

Learning Materials:

Textbooks:

1. Jon Duckett “Beginning Web Programming” WROX

2. Marty Hall and Larry Brown “Core Servlets and Java Server pages Vol. 1: Core Technologies”, Pearson

3. Sebesta, “Programming world wide web” Pearson.

4. Principles of Distributed Database Systems by M. Tamer Ozsu and Patrick Valduriez

5. Wang,“An Introduction to web Design and Programming”, Thomson

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Web Programming

Course Type: Theory Prerequisite: CSE 2121-0613, CSE 3223, CSE 1214-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

This course covers the tools and technology for developing web applications, the HTTP protocol, dynamic web programming, web application optimization, and security improvements, preparing you to become a full-stack web application developer.

Course Contents:

Web Servers, web browsers

HTML Introduction

HTML Syntax

HTML Head, Title

HTML Attributes, Headings, Paragraphs

HTML Links, Images

HTML Comments, Styles, Color, Tables

HTML Forms & their design etc.

Create web pages purely with HTML code.

CSS Introduction

PHP/JSP Introduction

PHP Syntax

PHP Variable, Echo, Data Types

PHP String, Constant, Operators

PHP If-Else, Switch, While, For Loops

PHP Form Handling & Validation

Connecting the website with the server using PHP

Retrieving, Inserting, Deleting, or Updating data using PHP

JavaScript Introduction

JavaScript Syntax

JavaScript Basics Variables, Operators, Arithmetic, etc

Different frameworks

Project Integration

Laboratory work / Experiments:

➢ Introduction to web servers and web browsers and mark-up language (HTML).

➢ Create web pages purely with HTML code.

➢ Create a web page to show applications of CSS files.

➢ Create a web page to show the application of form controls and design using Bootstrap

➢ Form validation and file handling in PHP/JSP/ASP.NET.

➢ PHP/JSP user management system

➢ Design a sample database

➢ Practice data definition language and data manipulation language

➢ Experiment with database connection and session and cookies in PHP/JSP/ASP.NET

➢ Study of JavaScript and applying JavaScript to web pages

➢ Create a web page with HTML, CSS, JavaScript & PHP/JSP/ASP.NET

➢ Study with the framework: LARAVEL/JSP/JSOUP/.NET

➢ Working on the team project with bitbucket and preparing a demo

➢ Working on the team project with bitbucket

** Bitbucket is a Git-based source code repository hosting service owned by Atlassian. Bitbucket offers both commercial plans and free accounts with an unlimited number of private repositories.

Course Learning Outcomes (CLOs):

CLO1: Demonstrate and comprehend the fundamentals of web programming.

CLO2: Using HTML and CSS code, create well-structured, readily maintainable, standards-compliant web pages.

CLO3: Add dynamic content to pages that match unique requirements and interests with JavaScript.

CLO4: To make dynamic pages, and form validation mechanisms, use the JavaScript frameworks jQuery and AngularJS and ensure client-side web security.

References:

Learning Materials:

Textbooks:

1. Jon Duckett “Beginning Web Programming” WROX

2. Marty Hall and Larry Brown “Core Servlets and Java Server pages Vol. 1: Core Technologies”, Pearson

3. Sebesta, “Programming world wide web” Pearson.

4. Principles of Distributed Database Systems by M. Tamer Ozsu and Patrick Valduriez

5. Wang,“An Introduction to web Design and Programming”, Thomson

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 3208-0613

Course Title: Integrated Design Project II

Course Type: Lab

Prerequisite: CSE 3108

Credits: 2

Contact Hours: 28

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

The major focus of this course is to combine engineering theory with rigorous research in the design and development of computerized systems considering ethical, technical, and financial issues. Based on the market analysis and documentation, design the system’s architecture and finally integrate hardware and software for making a completely viable product.

Course Outlines:

⮚ Able to complete detailed design & modeling

⮚ Prepare initial UI design and hardware connection

⮚ The complete whole implementation of software and hardware and integration of them together

⮚ Perform necessary testing & evaluate the system

⮚ Perform unit testing and integration testing with verification

⮚ Generate testing report

⮚ Final Submission

⮚ Final Observation & Correction

⮚ Evaluation Committee (Supervisor + Other members)

Course Learning Outcomes (CLOs):

CLO1: Design appropriate tests to measure and evaluate the performance of prototype subsystems considering ethical, financial, and environmental issues and recommend changes.

CLO2: Contribute to the accomplishments of a multidisciplinary team, including critical evaluation of self and team-member performance.

CLO3: Communicate the team’s logistical and technical approaches and be able to perform project management skills.

CLO4: Able to show a complete system consisting of hardware and software fulfilling the verification and validation.

References:

Learning Materials:

Textbooks:

1 Project Management, 4th edition, Stephen hartley

2 Software Requirements & Specifications, by Michael J. Jackson and Michael Jackson

Other Learning Materials: Problem-solving platforms, webinars, Web Materials

Course Title: Integrated Design Project II

Course Type: Lab

Prerequisite: CSE 3108

Credits: 2

Contact Hours: 28

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

The major focus of this course is to combine engineering theory with rigorous research in the design and development of computerized systems considering ethical, technical, and financial issues. Based on the market analysis and documentation, design the system’s architecture and finally integrate hardware and software for making a completely viable product.

Course Outlines:

⮚ Able to complete detailed design & modeling

⮚ Prepare initial UI design and hardware connection

⮚ The complete whole implementation of software and hardware and integration of them together

⮚ Perform necessary testing & evaluate the system

⮚ Perform unit testing and integration testing with verification

⮚ Generate testing report

⮚ Final Submission

⮚ Final Observation & Correction

⮚ Evaluation Committee (Supervisor + Other members)

Course Learning Outcomes (CLOs):

CLO1: Design appropriate tests to measure and evaluate the performance of prototype subsystems considering ethical, financial, and environmental issues and recommend changes.

CLO2: Contribute to the accomplishments of a multidisciplinary team, including critical evaluation of self and team-member performance.

CLO3: Communicate the team’s logistical and technical approaches and be able to perform project management skills.

CLO4: Able to show a complete system consisting of hardware and software fulfilling the verification and validation.

References:

Learning Materials:

Textbooks:

1 Project Management, 4th edition, Stephen hartley

2 Software Requirements & Specifications, by Michael J. Jackson and Michael Jackson

Other Learning Materials: Problem-solving platforms, webinars, Web Materials

Course Code: CSE 4125-0613

Course Title: Software Engineering

Course Type: Theory

Prerequisite: CSE 2121-0613, CSE 3246

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

Software Engineering is intended to assist students to grow and comprehend how to construct a software system development process, as well as to teach them the fundamental concepts of system development using object-oriented technology via the Use Case Model and the Object-Oriented Model. Students will be introduced to various software process models, project management, software requirements, and design as a problem-solving activity, important parts of analysis and design, and the role of the analysis and design stages within the system development life cycle.

Course Contents:

1. Software Engineering: Software Engineering Principles, Software Processes, SDLC, SDLC Models, Requirement Engineering

2. Models: Waterfall Model, RAD Model, Spiral Model, V-model, Incremental Model, Agile Model, Iterative Model, Big-Bang Model, Prototype Model

3. Software Management: Project Management, Activities, Project Management Tools

4. Software Metrics: Software Metrics, Size Oriented Metrics, Halstead's Software Metrics, Functional Point (FP) Analysis, Data Structure Metrics, Information Flow Metrics, Case Tools For Software Metrics

5. Project Planning: Software Project Planning, Software Cost Estimation, COCOMO Model

6. Risk Management: Risk Management Activities, Project Scheduling, Personnel Planning

7. Software Requirement: Software Requirement Specifications, Requirements Analysis, Data Flow Diagrams, Data Dictionaries, Entity-Relationship Diagram

8. S/W Configuration: Software Configuration Management, SCM Process, Software Quality Assurance, Project Monitoring & Control

9. Software Quality: ISO 9000 Certification, SEICMM, PCMM, Six Sigma

10. Software Design: Software Design Principles, Coupling, and Cohesion, Function Oriented Design, Object Oriented Design, User Interface Design

11. Software Reliability: Software Failure Mechanisms, Software Reliability Measurement Techniques, Software Reliability Metrics, Software Fault Tolerance

12. Software Reliability Models: Jelinski & Moranda Model, Basic Execution Time Model, Goel-Okumoto (GO) Model, Musa-Okumoto Logarithmic Model

13. Software Maintenance: Causes of Software Maintenance Problems, Software Maintenance Cost Factors

Course Learning Outcomes (CLOs):

CLO1: Able to explain a process model for software project development.

CLO2: Would be able to analyze and prepare SRS (Software Requirement Specification), design document, and project plan of a given software.

CLO3: Able to analyze the cost estimate and problem complexity using different estimation techniques.

CLO4: To be able to explain the advantages of configuration management and risk management activities.

CLO5: Able to build and maintain large-scale projects in a team environment.

References:

Learning Materials:

Textbooks:

1. Software Engineering A Practitioner's Approach by Roger S. Pressman, 7th edition, McGraw Hill, 2010.

2. Software Engineering by Ian Sommerville, 9th edition, Addison-Wesley, 2011

3. Software Engineering by Ivan Marsic

4. Software Engineering: Principles and Practice by Hans van Vliet

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Software Engineering

Course Type: Theory

Prerequisite: CSE 2121-0613, CSE 3246

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

Software Engineering is intended to assist students to grow and comprehend how to construct a software system development process, as well as to teach them the fundamental concepts of system development using object-oriented technology via the Use Case Model and the Object-Oriented Model. Students will be introduced to various software process models, project management, software requirements, and design as a problem-solving activity, important parts of analysis and design, and the role of the analysis and design stages within the system development life cycle.

Course Contents:

1. Software Engineering: Software Engineering Principles, Software Processes, SDLC, SDLC Models, Requirement Engineering

2. Models: Waterfall Model, RAD Model, Spiral Model, V-model, Incremental Model, Agile Model, Iterative Model, Big-Bang Model, Prototype Model

3. Software Management: Project Management, Activities, Project Management Tools

4. Software Metrics: Software Metrics, Size Oriented Metrics, Halstead's Software Metrics, Functional Point (FP) Analysis, Data Structure Metrics, Information Flow Metrics, Case Tools For Software Metrics

5. Project Planning: Software Project Planning, Software Cost Estimation, COCOMO Model

6. Risk Management: Risk Management Activities, Project Scheduling, Personnel Planning

7. Software Requirement: Software Requirement Specifications, Requirements Analysis, Data Flow Diagrams, Data Dictionaries, Entity-Relationship Diagram

8. S/W Configuration: Software Configuration Management, SCM Process, Software Quality Assurance, Project Monitoring & Control

9. Software Quality: ISO 9000 Certification, SEICMM, PCMM, Six Sigma

10. Software Design: Software Design Principles, Coupling, and Cohesion, Function Oriented Design, Object Oriented Design, User Interface Design

11. Software Reliability: Software Failure Mechanisms, Software Reliability Measurement Techniques, Software Reliability Metrics, Software Fault Tolerance

12. Software Reliability Models: Jelinski & Moranda Model, Basic Execution Time Model, Goel-Okumoto (GO) Model, Musa-Okumoto Logarithmic Model

13. Software Maintenance: Causes of Software Maintenance Problems, Software Maintenance Cost Factors

Course Learning Outcomes (CLOs):

CLO1: Able to explain a process model for software project development.

CLO2: Would be able to analyze and prepare SRS (Software Requirement Specification), design document, and project plan of a given software.

CLO3: Able to analyze the cost estimate and problem complexity using different estimation techniques.

CLO4: To be able to explain the advantages of configuration management and risk management activities.

CLO5: Able to build and maintain large-scale projects in a team environment.

References:

Learning Materials:

Textbooks:

1. Software Engineering A Practitioner's Approach by Roger S. Pressman, 7th edition, McGraw Hill, 2010.

2. Software Engineering by Ian Sommerville, 9th edition, Addison-Wesley, 2011

3. Software Engineering by Ivan Marsic

4. Software Engineering: Principles and Practice by Hans van Vliet

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 4126-0613

Course Title: Software Engineering Lab

Course Type: Lab

Prerequisite: CSE 2122-0613, CSE 3246

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

This course is designed to provide students with a comprehensive knowledge of software engineering beliefs and practices. It also involves an understanding of how to use software engineering methodologies to develop information systems.

List of Experiments:

➢ Define a group project and prepare a feasibility study report

➢ Do requirement analysis and Create a problem statement for a proposed project

➢ Develop Software Requirement Specification Sheet (SRS) for proposed systems

➢ Draw the diagram for product development: Entity Relationship(ER) Model, Data Flow Diagram (DFD), Context Flow Diagram (CFD)

➢ To perform the user‘s view analysis for the suggested system: Use a case diagram

➢ Prepare the structural view diagram for the system: Class diagram, object diagram

➢ Prepare the behavioral view diagram: State-chart diagram, Activity diagram

➢ Prepare the behavioral view diagram for the suggested system: Sequence diagram, Collaboration diagram

➢ To perform the implementation view diagram: Component diagram for the system.

➢ To perform the environmental view diagram: Deployment diagram for the system.

➢ To perform various testing using the testing tool unit testing, and integration testing for a sample code of the suggested system.

➢ Perform Estimation of effort using FP Estimation for the chosen system.

➢ To Prepare a timeline chart/Gantt Chart/PERT Chart for a selected software project.

➢ Develop the frontend and backend based on the proposed diagram and finalize the product.

➢ Product-based group presentation.

Course Learning Outcomes (CLOs):

CLO1: Able to know the software engineering methodologies involved in the phases of people management, process management, project planning, and product development.

CLO2: Able to gain knowledge about analysis, planning, development, and implementation in the industrial section.

CLO3: Able to develop software products personally as well as in a group environment.

CLO4: Able to use different tools, platforms, and software products and gain knowledge about society's demands.

Course Title: Software Engineering Lab

Course Type: Lab

Prerequisite: CSE 2122-0613, CSE 3246

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

This course is designed to provide students with a comprehensive knowledge of software engineering beliefs and practices. It also involves an understanding of how to use software engineering methodologies to develop information systems.

List of Experiments:

➢ Define a group project and prepare a feasibility study report

➢ Do requirement analysis and Create a problem statement for a proposed project

➢ Develop Software Requirement Specification Sheet (SRS) for proposed systems

➢ Draw the diagram for product development: Entity Relationship(ER) Model, Data Flow Diagram (DFD), Context Flow Diagram (CFD)

➢ To perform the user‘s view analysis for the suggested system: Use a case diagram

➢ Prepare the structural view diagram for the system: Class diagram, object diagram

➢ Prepare the behavioral view diagram: State-chart diagram, Activity diagram

➢ Prepare the behavioral view diagram for the suggested system: Sequence diagram, Collaboration diagram

➢ To perform the implementation view diagram: Component diagram for the system.

➢ To perform the environmental view diagram: Deployment diagram for the system.

➢ To perform various testing using the testing tool unit testing, and integration testing for a sample code of the suggested system.

➢ Perform Estimation of effort using FP Estimation for the chosen system.

➢ To Prepare a timeline chart/Gantt Chart/PERT Chart for a selected software project.

➢ Develop the frontend and backend based on the proposed diagram and finalize the product.

➢ Product-based group presentation.

Course Learning Outcomes (CLOs):

CLO1: Able to know the software engineering methodologies involved in the phases of people management, process management, project planning, and product development.

CLO2: Able to gain knowledge about analysis, planning, development, and implementation in the industrial section.

CLO3: Able to develop software products personally as well as in a group environment.

CLO4: Able to use different tools, platforms, and software products and gain knowledge about society's demands.

Course Code: CSE 4135-0612

Course Title: Cybersecurity and Law

Course Type: Theory

Prerequisite: CSE 2201

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

Cybersecurity Law is one of the most rapidly growing areas of law, and issues like privacy, cybercrime, international legal issues, and internet governance are some of the important areas that will be covered in this course. As a Computer Science and Engineering student, it is very important to have good knowledge of cybersecurity and law to avoid any kind of unethical and illegal issues for the benefit of myself and society.

Course Contents:

1. Introduction to Cybersecurity: Security principle: CIA Triad, Infamous Cybercrimes, Cybercrime Taxonomy, Civil vs Criminal Offenses.

2. Basic Elements of Criminal Law: Branches of Law, Tort Law, Cyberlaw enforcement, Cyberlaw Jurisdiction.

3. Overview of US Cybersecurity Law: History of Resolving Cybersecurity Disputes, Alternate Dispute Resolution, Data Breach Lawsuits.

4. Legal Doctrine: Duty of Care Doctrine, Failure to Act Doctrine, Reasonable Person Doctrine.

5. Procedural Law: Rules of Criminal Procedure, Computer Crime Laws, False Claim Act.

6. Data Privacy Law: Common Laws of Privacy, Privacy Laws, Data Breach Laws, and Data Breach Litigations.

7. Personal Security: Personal Liability, Directors and Officer’s Insurance, Preemptive Liability, Whistleblower Protections.

8. Data Encryption Law: Overview of Cryptology, Cryptology Law, International Cryptography Laws.

9. Standards and Regulations: International Statutes, Domestic Statutes, Industry Statutes.

10. Cybersecurity Law Program: Model and Architecture, Staffing and Roles, Policies and Procedures, Technology.

11. Cyber Liability Insurance: Coverage Categories, Policy Restrictions, Claim Processes.

12. Compliance Auditing: Critical Audit Matters, Internal vs External Auditing, Auditing Standards.

13. Developments in Cybersecurity Law: Future of Cyber Law, Impact of Technology on Cybersecurity Law.

14. International Cyber and Privacy Law: Harmonization of International Cyber laws, Cyber Treaties and Trade Pacts, Cyberlaw of the Sea and Space.

Course Learning Outcomes (CLOs):

CLO1: Learn the importance of cybersecurity on technology.

CLO2: Competent to identify and understand cybersecurity laws.

CLO3: Able to understand the impact of cybersecurity law on the industry and society.

References:

Learning Materials:

Textbooks:

1. Jeff Kosseff, Cybersecurity and Law, Publisher: Wiley

2. Schreider Tari, Cybersecurity Law, Standards and Regulations: 2nd Edition

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Cybersecurity and Law

Course Type: Theory

Prerequisite: CSE 2201

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

Cybersecurity Law is one of the most rapidly growing areas of law, and issues like privacy, cybercrime, international legal issues, and internet governance are some of the important areas that will be covered in this course. As a Computer Science and Engineering student, it is very important to have good knowledge of cybersecurity and law to avoid any kind of unethical and illegal issues for the benefit of myself and society.

Course Contents:

1. Introduction to Cybersecurity: Security principle: CIA Triad, Infamous Cybercrimes, Cybercrime Taxonomy, Civil vs Criminal Offenses.

2. Basic Elements of Criminal Law: Branches of Law, Tort Law, Cyberlaw enforcement, Cyberlaw Jurisdiction.

3. Overview of US Cybersecurity Law: History of Resolving Cybersecurity Disputes, Alternate Dispute Resolution, Data Breach Lawsuits.

4. Legal Doctrine: Duty of Care Doctrine, Failure to Act Doctrine, Reasonable Person Doctrine.

5. Procedural Law: Rules of Criminal Procedure, Computer Crime Laws, False Claim Act.

6. Data Privacy Law: Common Laws of Privacy, Privacy Laws, Data Breach Laws, and Data Breach Litigations.

7. Personal Security: Personal Liability, Directors and Officer’s Insurance, Preemptive Liability, Whistleblower Protections.

8. Data Encryption Law: Overview of Cryptology, Cryptology Law, International Cryptography Laws.

9. Standards and Regulations: International Statutes, Domestic Statutes, Industry Statutes.

10. Cybersecurity Law Program: Model and Architecture, Staffing and Roles, Policies and Procedures, Technology.

11. Cyber Liability Insurance: Coverage Categories, Policy Restrictions, Claim Processes.

12. Compliance Auditing: Critical Audit Matters, Internal vs External Auditing, Auditing Standards.

13. Developments in Cybersecurity Law: Future of Cyber Law, Impact of Technology on Cybersecurity Law.

14. International Cyber and Privacy Law: Harmonization of International Cyber laws, Cyber Treaties and Trade Pacts, Cyberlaw of the Sea and Space.

Course Learning Outcomes (CLOs):

CLO1: Learn the importance of cybersecurity on technology.

CLO2: Competent to identify and understand cybersecurity laws.

CLO3: Able to understand the impact of cybersecurity law on the industry and society.

References:

Learning Materials:

Textbooks:

1. Jeff Kosseff, Cybersecurity and Law, Publisher: Wiley

2. Schreider Tari, Cybersecurity Law, Standards and Regulations: 2nd Edition

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 4148-0723

Course Title: Mobile Application Development

Course Type: Lab

prerequisite: CSE 1214-0613, CSE 3246

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

The major focus of this course is to encourage students to learn to design and to build increasingly more sophisticated and meaningful mobile applications to understand the philosophy to improvise Android development building blocks and incorporate them with each other.

Lab Task:

➢ Rewinding of Object Oriented Programming concepts in JAVA.

➢ Problem Assessment of OOP Inheritance with some examples.

➢ Problem Assessment of OOP Exception Handling and Multiple Threading Concepts with some examples.

➢ Installation and Setting up the development environment of Android Studio and Java Development Kit.

➢ Creating the virtual emulator and initial configuration of the android SDK

➢ Create, compile and manifest the first “Hello World” Android app project.

➢ Introduction of Explicit and Implicit intents and solutions to intent challenges.

➢ Create an application of event handlers with onClick and onKeyDown.

➢ Introduction and Solution of Fragment, RecyclerView, and CardView

➢ Create an application with android user interface functions

➢ Create a simple android audio/video application

➢ Create android app widgets (display data from RSS feed)

➢ Introduction and Design of Backendless (Mobile Backend as a Service) and creating different features and layouts (eg. Login and Register activity, Password Reset, New Contact and Contact List Layout, Edit and Delete a contact

➢ Create an Application to create and query an SQLite Database.

➢ Android Technique on Data Storage and Retrieval from Android External Storage.

Course Learning Outcomes (CLOs):

CLO1: Able to identify the platform upon which Android Operating System can perform.

CLO2: Able to create and develop simple android applications.

CLO3: Able to create and access the database that can work with the application using multimedia under the android operating system.

Course Title: Mobile Application Development

Course Type: Lab

prerequisite: CSE 1214-0613, CSE 3246

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

The major focus of this course is to encourage students to learn to design and to build increasingly more sophisticated and meaningful mobile applications to understand the philosophy to improvise Android development building blocks and incorporate them with each other.

Lab Task:

➢ Rewinding of Object Oriented Programming concepts in JAVA.

➢ Problem Assessment of OOP Inheritance with some examples.

➢ Problem Assessment of OOP Exception Handling and Multiple Threading Concepts with some examples.

➢ Installation and Setting up the development environment of Android Studio and Java Development Kit.

➢ Creating the virtual emulator and initial configuration of the android SDK

➢ Create, compile and manifest the first “Hello World” Android app project.

➢ Introduction of Explicit and Implicit intents and solutions to intent challenges.

➢ Create an application of event handlers with onClick and onKeyDown.

➢ Introduction and Solution of Fragment, RecyclerView, and CardView

➢ Create an application with android user interface functions

➢ Create a simple android audio/video application

➢ Create android app widgets (display data from RSS feed)

➢ Introduction and Design of Backendless (Mobile Backend as a Service) and creating different features and layouts (eg. Login and Register activity, Password Reset, New Contact and Contact List Layout, Edit and Delete a contact

➢ Create an Application to create and query an SQLite Database.

➢ Android Technique on Data Storage and Retrieval from Android External Storage.

Course Learning Outcomes (CLOs):

CLO1: Able to identify the platform upon which Android Operating System can perform.

CLO2: Able to create and develop simple android applications.

CLO3: Able to create and access the database that can work with the application using multimedia under the android operating system.

Course Code: CSE 4137-0613

Course Title: Operating System

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

The Operating System course gives students a thorough grasp of today's operating systems. This course covers the fundamentals of operating system design and implementation. Here topics are not restricted to any single operating system or hardware platform. We will look at instances from many operating systems, including Unix/Linux and Windows. It also covers multiprocessor systems, virtualization, and cloud computing.

Course Contents:

1. Overview: Introduction, Software Execution, History, and Hardware, OS Structures

2. Process Management: Processes, Scheduling, Inter-process communication, Synchronization

3. Deadlock: Resource allocation and deadlock, deadlock detection, prevention, and recovery

4. Memory Management: Memory allocation, Paging, segmentation, Virtual memory

5. File System Management: File system interface, File system implementation

6. IO Management: IO systems, Disk management

7. File Systems: Files and directories, Security, Protection

Course Learning Outcomes (CLOs):

CLO1: Able to clarify and analyze the functions, facilities, structure, environment, and security of operating systems.

CLO2: Capable of researching operating system administrative operations and developing shell programs for process and file system administration with system calls.

CLO3: Ability to assess performance and apply various algorithms used in important operating system components such as the scheduler, memory manager, concurrency control manager, and mass-storage manager, as well as the I/O manager.

CLO4: Able to analyze and justify different device and resource management approaches, as well as controlling deadlock problems in time sharing and distributed systems.

References:

Learning Materials:

Textbooks:

1. Operating System Concepts, A. Silberschart, Peter B. Galvin and Greg Gagne, Published by Willey, 10th Edition.

2. Modern Operating Systems, Andrew S. Tanenbaum, Published by Pearson, 3rd Edition.

3. UNIX for Programmers and Users, Published by Pearson, 3rd Edition

4. Operating Systems, 3rd Edition by Gary Nutt, Pearson Education

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Operating System

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

The Operating System course gives students a thorough grasp of today's operating systems. This course covers the fundamentals of operating system design and implementation. Here topics are not restricted to any single operating system or hardware platform. We will look at instances from many operating systems, including Unix/Linux and Windows. It also covers multiprocessor systems, virtualization, and cloud computing.

Course Contents:

1. Overview: Introduction, Software Execution, History, and Hardware, OS Structures

2. Process Management: Processes, Scheduling, Inter-process communication, Synchronization

3. Deadlock: Resource allocation and deadlock, deadlock detection, prevention, and recovery

4. Memory Management: Memory allocation, Paging, segmentation, Virtual memory

5. File System Management: File system interface, File system implementation

6. IO Management: IO systems, Disk management

7. File Systems: Files and directories, Security, Protection

Course Learning Outcomes (CLOs):

CLO1: Able to clarify and analyze the functions, facilities, structure, environment, and security of operating systems.

CLO2: Capable of researching operating system administrative operations and developing shell programs for process and file system administration with system calls.

CLO3: Ability to assess performance and apply various algorithms used in important operating system components such as the scheduler, memory manager, concurrency control manager, and mass-storage manager, as well as the I/O manager.

CLO4: Able to analyze and justify different device and resource management approaches, as well as controlling deadlock problems in time sharing and distributed systems.

References:

Learning Materials:

Textbooks:

1. Operating System Concepts, A. Silberschart, Peter B. Galvin and Greg Gagne, Published by Willey, 10th Edition.

2. Modern Operating Systems, Andrew S. Tanenbaum, Published by Pearson, 3rd Edition.

3. UNIX for Programmers and Users, Published by Pearson, 3rd Edition

4. Operating Systems, 3rd Edition by Gary Nutt, Pearson Education

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 4138-0613

Course Title: Operating System Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

The course will investigate the significance of the operating system, its role, and the many strategies utilized by the operating system. Also understand how applications interact with operating systems, as well as how operating systems interact with machines. In addition, the course illuminated several of the currently available operating systems.

Lab Tasks:

➢ Basics of Unix commands

➢ Programs using the following system calls of Unix operating system

➢ Simple shell programs

➢ CPU scheduling algorithms

➢ Producer consumer problems using semaphores

➢ IPC using shared memory

➢ Bankers algorithm for deadlock avoidance

➢ Threading & synchronization applications

➢ Memory allocation methods for fixed partition

➢ Paging technique of memory management

➢ Page replacement algorithms.

➢ File organization technique

➢ File allocation strategies

Course Learning Outcomes (CLOs):

CLO1: Able to explain the functions, facilities, structure of operating systems, and fundamental operating system abstractions.

CLO2: Able to analyze the structure of the operating system and design the applications to run in parallel either using process or thread models of different OS.

CLO3: Able to analyze the performance and apply different algorithms used in major components of operating systems, such as scheduler, memory manager, concurrency control manager and mass-storage manager, I/O manager.

CLO4: Able to analyze and justify the various device and resource management techniques, managing deadlock situations for time-sharing and distributed systems.

Course Title: Operating System Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 3

Semester/Term: 2

Rationale:

The course will investigate the significance of the operating system, its role, and the many strategies utilized by the operating system. Also understand how applications interact with operating systems, as well as how operating systems interact with machines. In addition, the course illuminated several of the currently available operating systems.

Lab Tasks:

➢ Basics of Unix commands

➢ Programs using the following system calls of Unix operating system

➢ Simple shell programs

➢ CPU scheduling algorithms

➢ Producer consumer problems using semaphores

➢ IPC using shared memory

➢ Bankers algorithm for deadlock avoidance

➢ Threading & synchronization applications

➢ Memory allocation methods for fixed partition

➢ Paging technique of memory management

➢ Page replacement algorithms.

➢ File organization technique

➢ File allocation strategies

Course Learning Outcomes (CLOs):

CLO1: Able to explain the functions, facilities, structure of operating systems, and fundamental operating system abstractions.

CLO2: Able to analyze the structure of the operating system and design the applications to run in parallel either using process or thread models of different OS.

CLO3: Able to analyze the performance and apply different algorithms used in major components of operating systems, such as scheduler, memory manager, concurrency control manager and mass-storage manager, I/O manager.

CLO4: Able to analyze and justify the various device and resource management techniques, managing deadlock situations for time-sharing and distributed systems.

Course Code: CSE 4199-0613

Course Title: Project or Thesis I

Course Type: Theory

prerequisite: CSE 3108, CSE 3208

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course is intended to represent a project or thesis that motivates students to go neck-deep in industrial problem solutions as well as research that a new graduate can synthesize and make a point of view in different ways.

Course Learning Outcomes (CLOs):

CLO1: Able to plan, select, analyze and structure an engineering project to classify a particular field in considering the principles of sustainable design and development goals of national and international perspectives.

CLO2: Able to apply various hardware and software tools and techniques to solve real-life complex engineering problems under commitment to professional and ethical concerns.

CLO3: Ability to apply and develop robust project risk identification, effective communication, feasibility test, and assessment process as an individual and in multi-disciplinary and multi-cultural teams.

CLO4: Able to improvise the capability to undertake lifelong learning by analyzing real-world situations.

Course Title: Project or Thesis I

Course Type: Theory

prerequisite: CSE 3108, CSE 3208

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course is intended to represent a project or thesis that motivates students to go neck-deep in industrial problem solutions as well as research that a new graduate can synthesize and make a point of view in different ways.

Course Learning Outcomes (CLOs):

CLO1: Able to plan, select, analyze and structure an engineering project to classify a particular field in considering the principles of sustainable design and development goals of national and international perspectives.

CLO2: Able to apply various hardware and software tools and techniques to solve real-life complex engineering problems under commitment to professional and ethical concerns.

CLO3: Ability to apply and develop robust project risk identification, effective communication, feasibility test, and assessment process as an individual and in multi-disciplinary and multi-cultural teams.

CLO4: Able to improvise the capability to undertake lifelong learning by analyzing real-world situations.

Course Code: CSE 4299-0613

Course Title: Project or Thesis II

Course Type: Theory

prerequisite: CSE 3108, CSE 3208

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course is intended to represent a project or thesis that motivates students to go neck-deep in industrial problem solutions as well as research that a new graduate can synthesize and make a point of view in different ways.

Course Learning Outcomes (CLOs):

CLO1: Able to plan, select, analyze and structure an engineering project to classify a particular field in considering the principles of sustainable design and development goals of national and international perspectives.

CLO2: Able to apply various hardware and software tools and techniques to solve real-life complex engineering problems under commitment to professional and ethical concerns.

CLO3: Ability to apply and develop robust project risk identification, effective communication, feasibility test, and assessment process as an individual and in multi-disciplinary and multi-cultural teams.

CLO4: Able to improvise the capability to undertake lifelong learning by analyzing real-world situations.

Course Title: Project or Thesis II

Course Type: Theory

prerequisite: CSE 3108, CSE 3208

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course is intended to represent a project or thesis that motivates students to go neck-deep in industrial problem solutions as well as research that a new graduate can synthesize and make a point of view in different ways.

Course Learning Outcomes (CLOs):

CLO1: Able to plan, select, analyze and structure an engineering project to classify a particular field in considering the principles of sustainable design and development goals of national and international perspectives.

CLO2: Able to apply various hardware and software tools and techniques to solve real-life complex engineering problems under commitment to professional and ethical concerns.

CLO3: Ability to apply and develop robust project risk identification, effective communication, feasibility test, and assessment process as an individual and in multi-disciplinary and multi-cultural teams.

CLO4: Able to improvise the capability to undertake lifelong learning by analyzing real-world situations.

Course Code: CSE 4201-0612

Course Title: Data Mining and Machine Learning

Course Type: Theory

prerequisite: CSE 3224

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course covers data mining and machine learning techniques, as well as how to apply them to real-world datasets. Regression, classification, clustering, and association rule mining are the four core data mining techniques covered in this course. This course is also intended to implement machine learning techniques from a dataset.

Course Contents:

1. Introduction to Data Mining and Machine Learning: Applications of data mining, data mining tasks, motivation and challenges, types of data attributes and measurements, and data quality. Basic definitions, Hypothesis space and inductive bias, Bayes optimal classifier and Bayes error, Occam's razor, Curse of dimensionality, dimensionality reduction, feature scaling, and feature selection methods.

2. Data Pre-processing: Supervised and Unsupervised data, aggregation, sampling, dimensionality reduction, Feature Subset Selection, Feature Creation, Discretization and Binarization, and Variable Transformation.

3. Classification: Basic Concepts, Decision Tree Classifier: Decision tree algorithm, attribute selection measures, Nearest Neighbor Classifier, Bayes Theorem, and Naive Bayes Classifier, Perceptron, Multilayer perceptron, Neural networks, Back-propagation algorithm, Support Vector Machine (SVM, Kernel functions.

4. Model Evaluation: Holdout Method, Random Sub Sampling, Cross-Validation, evaluation metrics, confusion matrix.

5. Association Rule: Transaction data set, Frequent Itemset, Support measure, Apriori Principle, Apriori Algorithm, Computational Complexity, Rule Generation, Confidence of association rule.

6. Clustering: Basic Concepts, Different Types of Clustering Methods, Different Types of Clusters, K-means: The Basic K-means Algorithm, Strengths and Weaknesses of K-means algorithm, Agglomerative Hierarchical Clustering: Basic Algorithm, Proximity between clusters, 7. DBSCAN: The DBSCAN Algorithm, Strengths and Weaknesses.

8. Regression: Linear regression with one variable, linear regression with multiple variables, gradient descent, logistic regression, over-fitting, and regularization. performance evaluation metrics, validation methods.

Recommended Datasets for Practical:

1. UCI Machine Learning repository.

2. Kaggle

3. KDD Datasets

4. World Bank

Practical: Integrated Design Project / Capstone Project

Course Learning Outcomes (CLOs):

CLO1: Identifying data mining and machine learning preprocessing, cleaning, and transformation of data.

CLO2: Able to train the classifier and evaluate its performance, using a suitable classification algorithm.

CLO3: Apply the appropriate clustering algorithm to the data and assess the quality of the clustering.

CLO4: Able to use association rule mining methods to generate a large number of item sets and association rules on a regular basis.

CLO5: Able to solve complex problems based on regression algorithms.

References:

Learning Materials:

Textbooks:

1. Han, J., Kamber, M.,& Jian,P. (2011). Data Mining: Concepts and Techniques. 3rd edition. Morgan Kaufmann

2. Tan, P.-N., Steinbach, M., & Kumar, V. (2005). Introduction to Data Mining. 1st Edition. Pearson Education.

3. Flach, P. (2015). Machine Learning: The Art and Science of Algorithms that Make Sense of Data. Cambridge University Press.

4. Mitchell, T.M. (2017). Machine Learning. McGraw Hill Education.

5. Hand, D., & Mannila, H. & Smyth, P. (2006). Principles of Data Mining. Prentice-Hall of India

6. Pujari, A. (2008). Data Mining Techniques. 2nd edition. University Press.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Data Mining and Machine Learning

Course Type: Theory

prerequisite: CSE 3224

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course covers data mining and machine learning techniques, as well as how to apply them to real-world datasets. Regression, classification, clustering, and association rule mining are the four core data mining techniques covered in this course. This course is also intended to implement machine learning techniques from a dataset.

Course Contents:

1. Introduction to Data Mining and Machine Learning: Applications of data mining, data mining tasks, motivation and challenges, types of data attributes and measurements, and data quality. Basic definitions, Hypothesis space and inductive bias, Bayes optimal classifier and Bayes error, Occam's razor, Curse of dimensionality, dimensionality reduction, feature scaling, and feature selection methods.

2. Data Pre-processing: Supervised and Unsupervised data, aggregation, sampling, dimensionality reduction, Feature Subset Selection, Feature Creation, Discretization and Binarization, and Variable Transformation.

3. Classification: Basic Concepts, Decision Tree Classifier: Decision tree algorithm, attribute selection measures, Nearest Neighbor Classifier, Bayes Theorem, and Naive Bayes Classifier, Perceptron, Multilayer perceptron, Neural networks, Back-propagation algorithm, Support Vector Machine (SVM, Kernel functions.

4. Model Evaluation: Holdout Method, Random Sub Sampling, Cross-Validation, evaluation metrics, confusion matrix.

5. Association Rule: Transaction data set, Frequent Itemset, Support measure, Apriori Principle, Apriori Algorithm, Computational Complexity, Rule Generation, Confidence of association rule.

6. Clustering: Basic Concepts, Different Types of Clustering Methods, Different Types of Clusters, K-means: The Basic K-means Algorithm, Strengths and Weaknesses of K-means algorithm, Agglomerative Hierarchical Clustering: Basic Algorithm, Proximity between clusters, 7. DBSCAN: The DBSCAN Algorithm, Strengths and Weaknesses.

8. Regression: Linear regression with one variable, linear regression with multiple variables, gradient descent, logistic regression, over-fitting, and regularization. performance evaluation metrics, validation methods.

Recommended Datasets for Practical:

1. UCI Machine Learning repository.

2. Kaggle

3. KDD Datasets

4. World Bank

Practical: Integrated Design Project / Capstone Project

Course Learning Outcomes (CLOs):

CLO1: Identifying data mining and machine learning preprocessing, cleaning, and transformation of data.

CLO2: Able to train the classifier and evaluate its performance, using a suitable classification algorithm.

CLO3: Apply the appropriate clustering algorithm to the data and assess the quality of the clustering.

CLO4: Able to use association rule mining methods to generate a large number of item sets and association rules on a regular basis.

CLO5: Able to solve complex problems based on regression algorithms.

References:

Learning Materials:

Textbooks:

1. Han, J., Kamber, M.,& Jian,P. (2011). Data Mining: Concepts and Techniques. 3rd edition. Morgan Kaufmann

2. Tan, P.-N., Steinbach, M., & Kumar, V. (2005). Introduction to Data Mining. 1st Edition. Pearson Education.

3. Flach, P. (2015). Machine Learning: The Art and Science of Algorithms that Make Sense of Data. Cambridge University Press.

4. Mitchell, T.M. (2017). Machine Learning. McGraw Hill Education.

5. Hand, D., & Mannila, H. & Smyth, P. (2006). Principles of Data Mining. Prentice-Hall of India

6. Pujari, A. (2008). Data Mining Techniques. 2nd edition. University Press.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 4229-0613

Course Title: Artificial Intelligence

Course Type: Theory

prerequisite: CSE 1111-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

Artificial intelligence is a fast-moving technology and the beginning of a revolution with impacts and implications for the rational behavior of intelligent agents. It is a fundamental introduction to the building blocks and components of Artificial Intelligence along with knowledge perception and representation of different searching algorithms, machine learning, decision planning, reasoning, neural networks, learning, and understanding ideas to solve real-life complex situations.

Course Contents:

1. Introduction to Artificial Intelligence: What is Artificial Intelligence, Knowledge-based systems, Problem-solving by searching, Early Works of AI, Classic AI problems, Inference Engine

2. Classic AI Search Problems: 3*3*3 Rubik's Cube, Map Searching, 8 Puzzles Problem, N-Queens Problems, Different Problem Formulation, Goal Formulation, Constraint Satisfaction Problem, Backtracking Search, Back Propagation

3. Advanced Searching: Uninformed or Blind Search, Informed or Heuristic Search, Game Playing with Adversarial Search, Local Search

4. Knowledge Representation and Reasoning under Uncertainty: Declarative vs Procedural Search, Fundamental Concepts of Logical Representation, Propositional Logic, First Order Logic, Planning

5. Machine Learning, Robotics, Neural Networks, Expert Systems, Fuzzy Logic: Representation, Evaluation, Optimization, Supervised, Unsupervised, Semi-Supervised and Reinforcement Learning, Artificial and Multilayer Neural Network, Natural Language Generation, Terminology, Robot Locomotion, Components of Robot, Computer Vision, Fuzzy logic Systems.

Course Learning Outcomes (CLOs):

CLO1: Able to explain the historical background of AI and differentiate between various AI search algorithms, knowledge-based systems, and different characteristics of goal-based intelligent agents.

CLO2: Able to learn different logic formalisms, machine learning algorithms, robotics, and adversarial (game) algorithms.

CLO3: Able to analyze the structures, models, and core concepts of traditional information processing, natural language processing, deep learning, reinforcement learning, and its application to complex and human-centered problems.

CLO4: Competent to apply knowledge representation, and reasoning, and demonstrating practical experience by experimenting with real-world problems with the learning algorithms.

References

Learning Materials

Textbooks:

1. Stuart J. Russell and Peter Norvig, Artificial Intelligence: Modern Approach (new edition), USA, Prentice Hall, 2006

2. “Artificial Intelligence Illuminated” Ben Coppin, Jones and Bartlett illuminated Series, 2004

3. “Artificial Intelligence: A new synthesis” Nils Nilsson, Morgan Kaufmann, 1998

4. “Artificial Intelligence – Structures and Strategies for Complex problem solving", George F. Luger, Pearson International Edition, Sixth edition, 2009.

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Artificial Intelligence

Course Type: Theory

prerequisite: CSE 1111-0613

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

Artificial intelligence is a fast-moving technology and the beginning of a revolution with impacts and implications for the rational behavior of intelligent agents. It is a fundamental introduction to the building blocks and components of Artificial Intelligence along with knowledge perception and representation of different searching algorithms, machine learning, decision planning, reasoning, neural networks, learning, and understanding ideas to solve real-life complex situations.

Course Contents:

1. Introduction to Artificial Intelligence: What is Artificial Intelligence, Knowledge-based systems, Problem-solving by searching, Early Works of AI, Classic AI problems, Inference Engine

2. Classic AI Search Problems: 3*3*3 Rubik's Cube, Map Searching, 8 Puzzles Problem, N-Queens Problems, Different Problem Formulation, Goal Formulation, Constraint Satisfaction Problem, Backtracking Search, Back Propagation

3. Advanced Searching: Uninformed or Blind Search, Informed or Heuristic Search, Game Playing with Adversarial Search, Local Search

4. Knowledge Representation and Reasoning under Uncertainty: Declarative vs Procedural Search, Fundamental Concepts of Logical Representation, Propositional Logic, First Order Logic, Planning

5. Machine Learning, Robotics, Neural Networks, Expert Systems, Fuzzy Logic: Representation, Evaluation, Optimization, Supervised, Unsupervised, Semi-Supervised and Reinforcement Learning, Artificial and Multilayer Neural Network, Natural Language Generation, Terminology, Robot Locomotion, Components of Robot, Computer Vision, Fuzzy logic Systems.

Course Learning Outcomes (CLOs):

CLO1: Able to explain the historical background of AI and differentiate between various AI search algorithms, knowledge-based systems, and different characteristics of goal-based intelligent agents.

CLO2: Able to learn different logic formalisms, machine learning algorithms, robotics, and adversarial (game) algorithms.

CLO3: Able to analyze the structures, models, and core concepts of traditional information processing, natural language processing, deep learning, reinforcement learning, and its application to complex and human-centered problems.

CLO4: Competent to apply knowledge representation, and reasoning, and demonstrating practical experience by experimenting with real-world problems with the learning algorithms.

References

Learning Materials

Textbooks:

1. Stuart J. Russell and Peter Norvig, Artificial Intelligence: Modern Approach (new edition), USA, Prentice Hall, 2006

2. “Artificial Intelligence Illuminated” Ben Coppin, Jones and Bartlett illuminated Series, 2004

3. “Artificial Intelligence: A new synthesis” Nils Nilsson, Morgan Kaufmann, 1998

4. “Artificial Intelligence – Structures and Strategies for Complex problem solving", George F. Luger, Pearson International Edition, Sixth edition, 2009.

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 4230-0613

Course Title: Artificial Intelligence Lab

Course Type: Lab

prerequisite: CSE 1112-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

The major focus of this course is to explore the problem-solving paradigms through logic and theorem proving, search and control methods, and acquaintance with knowledge-based problem solving with relevant basic programs and their underlying theoretical concepts.

Lab Tasks:

➢ Introduction to Prolog Programming and orientation of practical life AI programming areas

➢ Queries, facts, and complex variable verification using Prolog Programming Language

➢ Complex Read-Write Problem demonstration in Prolog

➢ Finding Ancestor and Family Tree investigation problems in Prolog.

➢ Classic AI searching problem demonstration using 8-Puzzle Problem in Python.

➢ Manifestation of Uninformed Search using Breadth First Search in Python.

➢ Manifestation of Uninformed Search using Depth First Search in Python.

➢ Implementation of without heuristic methodology using Uniform Cost Search and Iterative Deepening Search

➢ Implementation of without Heuristic methodology using Bidirectional Search

➢ Greedy Best First Search Algorithm implementation using Informed Search Methodology.

➢ Classic AI searching problem demonstration using A* Search problem in Python.

➢ Adversarial Search Methodology in Game Playing Algorithm using Minimax Algorithm

➢ Adversarial Search Methodology in Game Playing Algorithm using α-ꞵ Algorithm

➢ Demonstration of Local Searching using various algorithm

➢ Introduction to Robotic Simulation in Artificial Intelligence

Course Learning Outcomes (CLOs):

CLO1: Able to categorize AI problem-based algorithms based on real-life manifestations and their constraints

CLO2: Able to implement mathematical models and adversarial algorithms.

CLO3: Competent to develop programming skills with traditional AI skills and applications.

Course Title: Artificial Intelligence Lab

Course Type: Lab

prerequisite: CSE 1112-0613

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

The major focus of this course is to explore the problem-solving paradigms through logic and theorem proving, search and control methods, and acquaintance with knowledge-based problem solving with relevant basic programs and their underlying theoretical concepts.

Lab Tasks:

➢ Introduction to Prolog Programming and orientation of practical life AI programming areas

➢ Queries, facts, and complex variable verification using Prolog Programming Language

➢ Complex Read-Write Problem demonstration in Prolog

➢ Finding Ancestor and Family Tree investigation problems in Prolog.

➢ Classic AI searching problem demonstration using 8-Puzzle Problem in Python.

➢ Manifestation of Uninformed Search using Breadth First Search in Python.

➢ Manifestation of Uninformed Search using Depth First Search in Python.

➢ Implementation of without heuristic methodology using Uniform Cost Search and Iterative Deepening Search

➢ Implementation of without Heuristic methodology using Bidirectional Search

➢ Greedy Best First Search Algorithm implementation using Informed Search Methodology.

➢ Classic AI searching problem demonstration using A* Search problem in Python.

➢ Adversarial Search Methodology in Game Playing Algorithm using Minimax Algorithm

➢ Adversarial Search Methodology in Game Playing Algorithm using α-ꞵ Algorithm

➢ Demonstration of Local Searching using various algorithm

➢ Introduction to Robotic Simulation in Artificial Intelligence

Course Learning Outcomes (CLOs):

CLO1: Able to categorize AI problem-based algorithms based on real-life manifestations and their constraints

CLO2: Able to implement mathematical models and adversarial algorithms.

CLO3: Competent to develop programming skills with traditional AI skills and applications.

Course Code: CSE 4163-0613

Course Title: Software Project Management

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Designing to help students track projects, tasks, milestones, and schedules. Ensures the overall proper organization of software projects and encourages teamwork on time. The main aspects of software project management are high-level project overview, task management, reporting, and time tracking. Project management is to bring about beneficial change or added value in repetitive, permanent, or semi-permanent functional activities to produce products or services, which requires the development of distinct technical skills and management strategies.

Course Contents:

Planning: Foundations of software project management, organization structure, and staffing, requirement analysis, motivation, authority and influence, conflict management, and proposal preparation.

Designing and Implementation: Build a prototype of the project, and architecture, analyze the pros and cons, implementation using the suitable framework, platforms, communication, security

Management: A large engineering software system management, client management, managing software project teams, project planning and scheduling, risk management, and configuration management.

Maintenance: Pricing estimation and cost control, quality assurance and accreditation, factors affecting software quality, software quality assurance plans, business context, and legal issues for software projects.

Testing: Software measurement: testing, upgrading and maintenance, testing network systems, and international project management.

Course Learning Outcomes (CLOs):

CLO1: Able to apply how to do proper planning and requirement analysis for organizing a software project.

CLO2: Competent to build logic sense or mechanism in different phases at the time of developing the software to solve a software project-related problem.

CLO3: Find out how to plan, schedule, and manage a project in a proper way and deliver it in due time.

CLO4: Competent to perform teamwork, participating in each stage of the project, project testing, troubleshooting, and assembling the overall project.

References:

Learning Materials:

Textbooks:

1. Murali K. Chemuturi and Thomas M. Cagley Jr., Mastering Software Project Management: Best Practices, Tools and Techniques, published by J. Ross Publishing.

2. Andrew Stellman and Jennifer Greene, Applied Software Project Management, published by O’Reilly Media.

Other Learning Materials: Web Materials, etc.

Course Title: Software Project Management

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Designing to help students track projects, tasks, milestones, and schedules. Ensures the overall proper organization of software projects and encourages teamwork on time. The main aspects of software project management are high-level project overview, task management, reporting, and time tracking. Project management is to bring about beneficial change or added value in repetitive, permanent, or semi-permanent functional activities to produce products or services, which requires the development of distinct technical skills and management strategies.

Course Contents:

Planning: Foundations of software project management, organization structure, and staffing, requirement analysis, motivation, authority and influence, conflict management, and proposal preparation.

Designing and Implementation: Build a prototype of the project, and architecture, analyze the pros and cons, implementation using the suitable framework, platforms, communication, security

Management: A large engineering software system management, client management, managing software project teams, project planning and scheduling, risk management, and configuration management.

Maintenance: Pricing estimation and cost control, quality assurance and accreditation, factors affecting software quality, software quality assurance plans, business context, and legal issues for software projects.

Testing: Software measurement: testing, upgrading and maintenance, testing network systems, and international project management.

Course Learning Outcomes (CLOs):

CLO1: Able to apply how to do proper planning and requirement analysis for organizing a software project.

CLO2: Competent to build logic sense or mechanism in different phases at the time of developing the software to solve a software project-related problem.

CLO3: Find out how to plan, schedule, and manage a project in a proper way and deliver it in due time.

CLO4: Competent to perform teamwork, participating in each stage of the project, project testing, troubleshooting, and assembling the overall project.

References:

Learning Materials:

Textbooks:

1. Murali K. Chemuturi and Thomas M. Cagley Jr., Mastering Software Project Management: Best Practices, Tools and Techniques, published by J. Ross Publishing.

2. Andrew Stellman and Jennifer Greene, Applied Software Project Management, published by O’Reilly Media.

Other Learning Materials: Web Materials, etc.

Course Code: CSE 4149-0612

Course Title: Data Science and Big Data Analytics

Course Type: Theory

prerequisite: CSE 2101, CSE 3104

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course covers fundamental concepts of Data, Data Mining, Data Science, and Big Data analysis and visualization in the field of exploratory data using Python/R. This will explore hidden knowledge from vast amounts of data.

Course Contents:

1. Fundamentals of Data Science: Introduction to Data Science, Data Science Life Cycle, Exploratory Data Analysis, Introduction to Jupyter Notebook, and motivation for using Python for data analysis. What do Data Scientists do?

2. Data Preparation: Concepts of Data and Big Data, Variables, Dataset, Database, Extraction, Transformation, and Loading (ETL)

3. Exploration: Univariate and Bivariate

4. Modeling: Classification, Regression, Clustering and Association Rules

5. Python Libraries: NumPy, pandas, matplotlib, SciPy, scikit-learn, statsmodels.

6. Working with Pandas: Arrays and vectorized computation, Introduction to pandas Data Structures, Essential Functionality, Summarizing and Computing Descriptive Statistics. Data Loading, Storage, and File Formats. Reading and Writing Data in Text Format, Web Scraping, Binary Data Formats, Interacting with Web APIs, Interacting with Databases

Data Cleaning and Preparation. Handling Missing Data, Data Transformation, and String Manipulation.

7. Data Wrangling: Hierarchical Indexing, Combining and Merging Data Sets Reshaping and Pivoting.

8. Data Visualization: Basics of matplotlib, plotting with pandas and seaborn, and other python visualization tools.

9. Data Aggregation and Group operations: Group by Mechanics, Data aggregation, General split-apply-combine, Pivot tables, and cross-tabulation.

10. Time Series Data Analysis: Date and Time Data Types and Tools, Time series Basics, date Ranges, Frequencies and Shifting, Time Zone Handling, Periods and Periods Arithmetic, Resampling and Frequency conversion, and Moving Window Functions.

11. Advanced Pandas: Categorical Data, Advanced GroupBy Use, Techniques for Method Chaining.

Recommended Datasets for Practical:

1. UCI Machine Learning repository.

2. Kaggle

3. KDD Datasets

4. World Bank

Practical :

➢ NumPy and array-based practicals

➢ Experiments with Pandas Data Structures

➢ Data Loading, Storage, and File Formats Practicals

➢ Practicals based on Web API Interaction

➢ Data Cleaning and Preparation-Based Practicals

➢ Data Wrangling-Based Practicals

➢ Practicals based on Matplotlib Data Visualization

➢ Data Aggregation-Based Practicals

➢ Time Series Data Analysis Applications

Course Learning Outcomes (CLOs):

CLO1: Fundamental concepts of Data Science and Big Data. To Utilize the pandas' library's data analysis tools.

CLO2: Able to data loading, cleaning, transformation, merging, and reshaping are all things you can do with it.

CLO3: Able to visualize and summarize data sets in a way that is both instructive and concise.

CLO4: Able to time series data must be analyzed and manipulated.

CLO5: Able to solve data analysis challenges in the real world.

References:

Learning Materials:

Textbooks:

1. McKinney, W.(2017). Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. 2nd edition. O’Reilly Media.

2. O’Neil, C., & Schutt, R. (2013). Doing Data Science: Straight Talk from the Frontline O’Reilly Media

Other Learning Materials: Journals, Web Materials, etc.

http://www.saedsayad.com/data_mining_map.htm

Course Title: Data Science and Big Data Analytics

Course Type: Theory

prerequisite: CSE 2101, CSE 3104

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course covers fundamental concepts of Data, Data Mining, Data Science, and Big Data analysis and visualization in the field of exploratory data using Python/R. This will explore hidden knowledge from vast amounts of data.

Course Contents:

1. Fundamentals of Data Science: Introduction to Data Science, Data Science Life Cycle, Exploratory Data Analysis, Introduction to Jupyter Notebook, and motivation for using Python for data analysis. What do Data Scientists do?

2. Data Preparation: Concepts of Data and Big Data, Variables, Dataset, Database, Extraction, Transformation, and Loading (ETL)

3. Exploration: Univariate and Bivariate

4. Modeling: Classification, Regression, Clustering and Association Rules

5. Python Libraries: NumPy, pandas, matplotlib, SciPy, scikit-learn, statsmodels.

6. Working with Pandas: Arrays and vectorized computation, Introduction to pandas Data Structures, Essential Functionality, Summarizing and Computing Descriptive Statistics. Data Loading, Storage, and File Formats. Reading and Writing Data in Text Format, Web Scraping, Binary Data Formats, Interacting with Web APIs, Interacting with Databases

Data Cleaning and Preparation. Handling Missing Data, Data Transformation, and String Manipulation.

7. Data Wrangling: Hierarchical Indexing, Combining and Merging Data Sets Reshaping and Pivoting.

8. Data Visualization: Basics of matplotlib, plotting with pandas and seaborn, and other python visualization tools.

9. Data Aggregation and Group operations: Group by Mechanics, Data aggregation, General split-apply-combine, Pivot tables, and cross-tabulation.

10. Time Series Data Analysis: Date and Time Data Types and Tools, Time series Basics, date Ranges, Frequencies and Shifting, Time Zone Handling, Periods and Periods Arithmetic, Resampling and Frequency conversion, and Moving Window Functions.

11. Advanced Pandas: Categorical Data, Advanced GroupBy Use, Techniques for Method Chaining.

Recommended Datasets for Practical:

1. UCI Machine Learning repository.

2. Kaggle

3. KDD Datasets

4. World Bank

Practical :

➢ NumPy and array-based practicals

➢ Experiments with Pandas Data Structures

➢ Data Loading, Storage, and File Formats Practicals

➢ Practicals based on Web API Interaction

➢ Data Cleaning and Preparation-Based Practicals

➢ Data Wrangling-Based Practicals

➢ Practicals based on Matplotlib Data Visualization

➢ Data Aggregation-Based Practicals

➢ Time Series Data Analysis Applications

Course Learning Outcomes (CLOs):

CLO1: Fundamental concepts of Data Science and Big Data. To Utilize the pandas' library's data analysis tools.

CLO2: Able to data loading, cleaning, transformation, merging, and reshaping are all things you can do with it.

CLO3: Able to visualize and summarize data sets in a way that is both instructive and concise.

CLO4: Able to time series data must be analyzed and manipulated.

CLO5: Able to solve data analysis challenges in the real world.

References:

Learning Materials:

Textbooks:

1. McKinney, W.(2017). Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. 2nd edition. O’Reilly Media.

2. O’Neil, C., & Schutt, R. (2013). Doing Data Science: Straight Talk from the Frontline O’Reilly Media

Other Learning Materials: Journals, Web Materials, etc.

http://www.saedsayad.com/data_mining_map.htm

Course Code: CSE 4164-0613

Course Title: Basic Graph Theory

Course Type: Theory

Credits:3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Every sophisticated system started simple. Before advanced network modeling, this course focused on basic graph theory and analysis. But now, the study also covers concepts and approaches for network analysis. This course examines graph theoretical topics and challenges and algorithmic applications of graph theory. The course explores the fundamentals of graph theory, focusing on trees and bipartite graphs. The course covers algorithms for solving graph-theoretic problems. An illustration would be locating a maximum weight match or network flow. Graph theory examines graphs, trees, and networks. Topics include.

Course Contents:

1. Fundamentals of Graph theory: Graphs and their applications, Basic graph terminologies, Basic operations on graphs, Graph representations, Degree sequence, and graphic sequence.

2. Theory of Trees: Paths, cycles, and connectivity; Trees and counting of trees; Distance in graphs and trees.

3. Algorithms: The Euler formula, Hamilton routes, planar graphs, Ear decomposition; Graph coloring;

4. Graph Problems: Graph labeling: Matching and covering, trees in sorting and prefix codes;

5. Methods: Network methods have the shortest path methodology, the minimal spanning tree technique, and Special classes of graphs.

Course Learning Outcomes (CLOs):

CLO1: Able to utilize the graph theory definitions to identify examples and distinguish them from objects that are not examples.

CLO2: In problem-solving, competent to apply theories and concepts to test and confirm intuition and independent mathematical reasoning.

CLO3: Able to integrate fundamental graph theory knowledge to address challenges.

CLO4: Can construct mathematical proofs by deducing conclusions from definitions.

CLO5: Can analyze new networks by applying the fundamental ideas of graph theory and how to read and write about graph theory in a consistent and technically accurate way with a team.

References:

Learning Materials:

Textbooks;

1. NarsinghDeo, Graph Theory with Applications to Engineering and Computer Science, Published by Prentice-Hall of India Pvt Ltd.

2. Douglas B. West, Introduction to Graph Theory, Published by Pearson, 2nd Edition.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Basic Graph Theory

Course Type: Theory

Credits:3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Every sophisticated system started simple. Before advanced network modeling, this course focused on basic graph theory and analysis. But now, the study also covers concepts and approaches for network analysis. This course examines graph theoretical topics and challenges and algorithmic applications of graph theory. The course explores the fundamentals of graph theory, focusing on trees and bipartite graphs. The course covers algorithms for solving graph-theoretic problems. An illustration would be locating a maximum weight match or network flow. Graph theory examines graphs, trees, and networks. Topics include.

Course Contents:

1. Fundamentals of Graph theory: Graphs and their applications, Basic graph terminologies, Basic operations on graphs, Graph representations, Degree sequence, and graphic sequence.

2. Theory of Trees: Paths, cycles, and connectivity; Trees and counting of trees; Distance in graphs and trees.

3. Algorithms: The Euler formula, Hamilton routes, planar graphs, Ear decomposition; Graph coloring;

4. Graph Problems: Graph labeling: Matching and covering, trees in sorting and prefix codes;

5. Methods: Network methods have the shortest path methodology, the minimal spanning tree technique, and Special classes of graphs.

Course Learning Outcomes (CLOs):

CLO1: Able to utilize the graph theory definitions to identify examples and distinguish them from objects that are not examples.

CLO2: In problem-solving, competent to apply theories and concepts to test and confirm intuition and independent mathematical reasoning.

CLO3: Able to integrate fundamental graph theory knowledge to address challenges.

CLO4: Can construct mathematical proofs by deducing conclusions from definitions.

CLO5: Can analyze new networks by applying the fundamental ideas of graph theory and how to read and write about graph theory in a consistent and technically accurate way with a team.

References:

Learning Materials:

Textbooks;

1. NarsinghDeo, Graph Theory with Applications to Engineering and Computer Science, Published by Prentice-Hall of India Pvt Ltd.

2. Douglas B. West, Introduction to Graph Theory, Published by Pearson, 2nd Edition.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 4172-0714

Course Title: Internet of Things

Course Type: Theory

prerequisite: CSE 2101, CSE 3106

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

The goal of this course is to enhance students’ understanding of the design and development of the Internet of Things (IoT) systems, including its architecture, technologies on each layer, and IoT-specific data processing and analytics frameworks. Hands-on skills will be developed by studying applications of IoT in every corner of life and implementing components of IoT applications.

Course Contents:

1. Introduction: Wireless Networking History, Wireless Certifications, Standard Organizations, WiFi Alliance, 802.11 Standards

2. Wireless Basics: How Wireless Works, Wireless SWOTs, Wireless Signal Characteristics, Wireless Topologies

3. Understanding RF: RF Behaviors, RF Math, Rule of 10s and 3s, Understanding Beamwidth

4. Wireless Signaling: Bands Channels and Frequencies, What is Spread Spectrum, Common Wireless bands, 2.4 GHz Basics, 5 GHz Basics, Bandwidth and Throughput

5. Signal Transmission: Antenna Basics, Radiation Patterns, Parabolic and Grid Antennas, MIMO, Understanding of Attenuators

6. Wireless LANs: Wireless LAN Basics, Access Point Basics, SSID Basics, BSS and BSSID, Access Point Modes, CSMA/CD, and CSMA/CA

7. Wireless Security Fundamentals: Wireless Security Challenges, Wireless Security Policy, AAA, Data Protection, WEP, WPA and WPA2, MAC Filtering

8. WLAN Design: Site Survey, Customer Education, Security Requirements, AP Placement, and Settings, Coverage Analysis

Course Learning Outcomes (CLOs):

CLO1: Learn the basic technological concept of Wireless Network

CLO2: Competent to understand the design and operation methodologies of Wireless Networks.

CLO3: Able to design a wireless network.

CLO4: Able to gain a solid understanding of how Wireless Network is solving variant complex engineering problems related to communication technologies.

References:

Learning Materials:

Textbooks:

1. Matthew Gaust, 802.11 Wireless Networks: The Definitive Guide

2. Adeel Javed, Building Arduino Projects for the Internet of Things: Experiments with Real World Applications, Published by Apress

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Internet of Things

Course Type: Theory

prerequisite: CSE 2101, CSE 3106

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

The goal of this course is to enhance students’ understanding of the design and development of the Internet of Things (IoT) systems, including its architecture, technologies on each layer, and IoT-specific data processing and analytics frameworks. Hands-on skills will be developed by studying applications of IoT in every corner of life and implementing components of IoT applications.

Course Contents:

1. Introduction: Wireless Networking History, Wireless Certifications, Standard Organizations, WiFi Alliance, 802.11 Standards

2. Wireless Basics: How Wireless Works, Wireless SWOTs, Wireless Signal Characteristics, Wireless Topologies

3. Understanding RF: RF Behaviors, RF Math, Rule of 10s and 3s, Understanding Beamwidth

4. Wireless Signaling: Bands Channels and Frequencies, What is Spread Spectrum, Common Wireless bands, 2.4 GHz Basics, 5 GHz Basics, Bandwidth and Throughput

5. Signal Transmission: Antenna Basics, Radiation Patterns, Parabolic and Grid Antennas, MIMO, Understanding of Attenuators

6. Wireless LANs: Wireless LAN Basics, Access Point Basics, SSID Basics, BSS and BSSID, Access Point Modes, CSMA/CD, and CSMA/CA

7. Wireless Security Fundamentals: Wireless Security Challenges, Wireless Security Policy, AAA, Data Protection, WEP, WPA and WPA2, MAC Filtering

8. WLAN Design: Site Survey, Customer Education, Security Requirements, AP Placement, and Settings, Coverage Analysis

Course Learning Outcomes (CLOs):

CLO1: Learn the basic technological concept of Wireless Network

CLO2: Competent to understand the design and operation methodologies of Wireless Networks.

CLO3: Able to design a wireless network.

CLO4: Able to gain a solid understanding of how Wireless Network is solving variant complex engineering problems related to communication technologies.

References:

Learning Materials:

Textbooks:

1. Matthew Gaust, 802.11 Wireless Networks: The Definitive Guide

2. Adeel Javed, Building Arduino Projects for the Internet of Things: Experiments with Real World Applications, Published by Apress

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 4171-0613

Course Title: Cloud Computing

Course Type: Theory

prerequisite: CSE 2201

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Cloud Computing is the next big thing in this era so it is an important topic to study for a student of Computer Science and Engineering. This course introduces students to the core concepts of cloud computing. Students can learn the fundamental knowledge required to understand Cloud Computing, its definition and characteristics, the problem it’s solving, Service Models, Service providers and a lot more from this course.

Course Contents:

1. Overview of Distributed Computing: Trends of Computing, Introduction to Distributed Computing, Next Big Thing: Cloud Computing.

Introduction: Introduction to Cloud Computing, Cloud Deployment Models, Types of Cloud, Cloud Provider

2. Attributes of Cloud Computing: Multi-tenancy, Massive Scalability, Elasticity

Infrastructure-as-a-Service(IaaS): Introduction to IaaS, Resource, Virtualization, Case Studies

3. Platform-as-a-Service(PaaS): Introduction to PaaS, Cloud Platform, Management of Computation and Storage, Case Studies.

4. Software-as-a-Service(SaaS): Introduction to SaaS, Web Services, Web 2.0, Web OS, Case Studies.

Cloud Issues and Challenges: Cloud Provider Lock-in or Vendor Lock-in, Security of Cloud Computing, Research about the latest issues with cloud computing.

Course Learning Outcomes (CLOs):

CLO1: Learn the fundamentals of cloud computing

CLO2: Competent to identify the architecture and infrastructure of cloud computing.

CLO3: Able to explain the core issues of cloud computing such as privacy, security, and interoperability.

CLO4: Competent to research and attempt to generate new ideas and innovations in cloud computing.

References:

Learning Materials:

Textbooks:

1. Barrie Sosinsky.Cloud Computing Bible. Wiley, 1st edition, 2011

2. John Rhoton. Cloud Computing Explained: Implementation Handbook for Enterprises, Recursive Press, 1st edition 2009.

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Cloud Computing

Course Type: Theory

prerequisite: CSE 2201

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Cloud Computing is the next big thing in this era so it is an important topic to study for a student of Computer Science and Engineering. This course introduces students to the core concepts of cloud computing. Students can learn the fundamental knowledge required to understand Cloud Computing, its definition and characteristics, the problem it’s solving, Service Models, Service providers and a lot more from this course.

Course Contents:

1. Overview of Distributed Computing: Trends of Computing, Introduction to Distributed Computing, Next Big Thing: Cloud Computing.

Introduction: Introduction to Cloud Computing, Cloud Deployment Models, Types of Cloud, Cloud Provider

2. Attributes of Cloud Computing: Multi-tenancy, Massive Scalability, Elasticity

Infrastructure-as-a-Service(IaaS): Introduction to IaaS, Resource, Virtualization, Case Studies

3. Platform-as-a-Service(PaaS): Introduction to PaaS, Cloud Platform, Management of Computation and Storage, Case Studies.

4. Software-as-a-Service(SaaS): Introduction to SaaS, Web Services, Web 2.0, Web OS, Case Studies.

Cloud Issues and Challenges: Cloud Provider Lock-in or Vendor Lock-in, Security of Cloud Computing, Research about the latest issues with cloud computing.

Course Learning Outcomes (CLOs):

CLO1: Learn the fundamentals of cloud computing

CLO2: Competent to identify the architecture and infrastructure of cloud computing.

CLO3: Able to explain the core issues of cloud computing such as privacy, security, and interoperability.

CLO4: Competent to research and attempt to generate new ideas and innovations in cloud computing.

References:

Learning Materials:

Textbooks:

1. Barrie Sosinsky.Cloud Computing Bible. Wiley, 1st edition, 2011

2. John Rhoton. Cloud Computing Explained: Implementation Handbook for Enterprises, Recursive Press, 1st edition 2009.

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 4168-0613

Course Title: Bioinformatics

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Introducing students to the fundamentals of evolution, molecular biology, and molecular evolution. Bioinformatics tools aid in analyzing, comparing, and interpreting genetic and genomic data and more generally in the explanation of evolutionary aspects of molecular biology. At a more integrative level, it helps analyze and catalog the biological pathways and networks.

Course Contents:

1. Introduction to Bioinformatics: Introduction to biology, biological databases, and high-throughput data sources; Overview of bioinformatics problems

2. Sequence Analysis and Alignment: Statistical significance of alignments; Suffix Trees; Suffix Arrays; Patterns, Profiles, and Multiple Alignments; Hidden Markov Models; Multiple Sequence Alignment Algorithms

3. Introduction to Protein Structures: Protein Structure Prediction; Structural Alignment of Proteins; Microarray data normalization, analysis of Clustering techniques

4. Introduction to Systems Biology: Gene regulatory networks

5. Construction and Analysis of Protein Networks: Monte Carlo Sampling, Random Walks on Graphs.

Course Learning Outcomes (CLOs):

CLO1: Able to demonstrate the core concepts of bioinformatics which includes computational biology, molecular biology, genomics, etc.

CLO2: Able to use critical thinking and fundamental use of probability and statistics in bioinformatics to get the explanation of experimental and computational data.

CLO3: Competent to explain the methods to characterize, classify and manage the different types of Biological data

CLO4: Competent to explore the basics of sequence alignment and analysis and get an overview of biological macromolecular structures and structure prediction methods.

References:

Learning Materials:

Textbooks:

1 D.E. Krane and M.L. Raymer, Fundamental Concepts of Bioinformatics, Pearson Education, 2003. Web Materials, etc.

2 N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT Press, 2004.

3 C.A. Orengo, D.T. Jones, and J.M.Thornton, Bioinformatics: Genes, Proteins and Computers, Routledge, 2003.

4 D. Mount, Bioinformatics: Sequence and genome analysis, Cold Spring Harbor Laboratory Press, 2001.

Other Learning Materials: Web Materials, etc.

Course Title: Bioinformatics

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Introducing students to the fundamentals of evolution, molecular biology, and molecular evolution. Bioinformatics tools aid in analyzing, comparing, and interpreting genetic and genomic data and more generally in the explanation of evolutionary aspects of molecular biology. At a more integrative level, it helps analyze and catalog the biological pathways and networks.

Course Contents:

1. Introduction to Bioinformatics: Introduction to biology, biological databases, and high-throughput data sources; Overview of bioinformatics problems

2. Sequence Analysis and Alignment: Statistical significance of alignments; Suffix Trees; Suffix Arrays; Patterns, Profiles, and Multiple Alignments; Hidden Markov Models; Multiple Sequence Alignment Algorithms

3. Introduction to Protein Structures: Protein Structure Prediction; Structural Alignment of Proteins; Microarray data normalization, analysis of Clustering techniques

4. Introduction to Systems Biology: Gene regulatory networks

5. Construction and Analysis of Protein Networks: Monte Carlo Sampling, Random Walks on Graphs.

Course Learning Outcomes (CLOs):

CLO1: Able to demonstrate the core concepts of bioinformatics which includes computational biology, molecular biology, genomics, etc.

CLO2: Able to use critical thinking and fundamental use of probability and statistics in bioinformatics to get the explanation of experimental and computational data.

CLO3: Competent to explain the methods to characterize, classify and manage the different types of Biological data

CLO4: Competent to explore the basics of sequence alignment and analysis and get an overview of biological macromolecular structures and structure prediction methods.

References:

Learning Materials:

Textbooks:

1 D.E. Krane and M.L. Raymer, Fundamental Concepts of Bioinformatics, Pearson Education, 2003. Web Materials, etc.

2 N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT Press, 2004.

3 C.A. Orengo, D.T. Jones, and J.M.Thornton, Bioinformatics: Genes, Proteins and Computers, Routledge, 2003.

4 D. Mount, Bioinformatics: Sequence and genome analysis, Cold Spring Harbor Laboratory Press, 2001.

Other Learning Materials: Web Materials, etc.

Course Code: CSE 4169-0714

Course Title: Robotics

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Defining fundamentals of robot working, programming, and integration in a manufacturing process. Designing, constructing, and using machines (robots) so that some tasks can be performed that are traditionally done by human beings. To perform repetitive simple tasks in industries or many other sectors where the environment is hazardous/not suitable for humans.

Course Contents:

1. Introduction: Historical evolution of robotics, Importance of material goods production in modern society, Robot's role in modern production, State of the art in industrial robotics, IFR statistics

2. Mechanics of Robotics: Robot characteristics, subsystems, and classification, Robot mechanical system: links, bearings, shafts, gearboxes, grippers

3. Robot Power and Control System: Electrical, pneumatic and hydraulic motors, Robot measuring system, Internal sensing: position, velocity, acceleration, force, External robot sensing: proximity sensors, range finders, tactile sensors, vision.

4. Robot Kinematics: Joint and Cartesian space, homogeneous transformation, frames, and standard names, Denavit-Hartenberg notation, direct and inverse kinematics solution, Euler angles, Jacobian matrix, and velocity transformation, Robot trajectory planning in joint and Cartesian space

5. Robot Dynamics: Forward and Inverse Dynamic, Euler-Lagrange formulation, joint and Cartesian forces, Equations of motion using Euler-Lagrange formulation, Newton-Euler formulation

6. Sensors: Contact and Proximity, Position, Velocity, Force, Tactile, etc., Introduction to Cameras, Camera calibration, Geometry of Image formation, Euclidean/Similarity/Affine/Projective transformations, Vision applications in robotics.

7. Robot Actuation Systems: Actuators: Electric, Hydraulic, and Pneumatic; Transmission: Gears, Timing Belts and Bearings, Parameters for selection of actuators.

8. Robot Control: Decoupling of nonlinear systems, feedforward and feedback control, control models and strategies, position control and simple feedback synthesis, adaptive control and force control

9. Control Hardware and Interfacing: Embedded systems: Microcontroller Architecture and integration with sensors, actuators, components, Programming Applications for Industrial robot - programming in – VAL II

10. Robot Programming: Motion-oriented and task-oriented languages, Robot application in typical operations and tasks, Mobile robots kinematics, path planning, and control, Research, and the future of robotics.

11. AI in Robotics: Applications in unmanned systems, defense, medical, industries, etc.

12. Application of Robotics: Robotics and Automation for Industry, Robot safety, and social robotics.

Course Learning Outcomes (CLOs):

CLO1: Able to explore the history of robotics, its importance, recent development in this sector, and modern production.

CLO2: Able to apply the knowledge of physics and mathematics involved in the design, construction, and control of robots, with a focus on linear algebra and geometry.

CLO3: Competent to find out the fundamental concepts of electrical and mechanical engineering and their tools that will help them better understand the design and development challenges in the field of robotics.

CLO4: Competent to perform an engineering design task that sharpens analytical, planning, presentation, and teamwork skills.

CLO5: Able to develop and deepen the programming concepts related to robotics.

References:

Learning Materials:

Textbooks:

1. Bruno Siciliano and OussamaKhatib, Springer Handbook of Robotics, Published by Springer, 2008.

2. Roland Siegwart, Illah Reza Nourbakhsh, and DavideScaramuzza, Introduction to Autonomous Mobile Robots, Published by The MIT Press, 2011

3. Robotic Engineering : An Integrated Approach” by Chmielewski and Klafter

4. “Robotics for Engineers” by Y Koren

5. “Introduction to Robotics” by J J Craig

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Robotics

Course Type: Theory

Prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

Defining fundamentals of robot working, programming, and integration in a manufacturing process. Designing, constructing, and using machines (robots) so that some tasks can be performed that are traditionally done by human beings. To perform repetitive simple tasks in industries or many other sectors where the environment is hazardous/not suitable for humans.

Course Contents:

1. Introduction: Historical evolution of robotics, Importance of material goods production in modern society, Robot's role in modern production, State of the art in industrial robotics, IFR statistics

2. Mechanics of Robotics: Robot characteristics, subsystems, and classification, Robot mechanical system: links, bearings, shafts, gearboxes, grippers

3. Robot Power and Control System: Electrical, pneumatic and hydraulic motors, Robot measuring system, Internal sensing: position, velocity, acceleration, force, External robot sensing: proximity sensors, range finders, tactile sensors, vision.

4. Robot Kinematics: Joint and Cartesian space, homogeneous transformation, frames, and standard names, Denavit-Hartenberg notation, direct and inverse kinematics solution, Euler angles, Jacobian matrix, and velocity transformation, Robot trajectory planning in joint and Cartesian space

5. Robot Dynamics: Forward and Inverse Dynamic, Euler-Lagrange formulation, joint and Cartesian forces, Equations of motion using Euler-Lagrange formulation, Newton-Euler formulation

6. Sensors: Contact and Proximity, Position, Velocity, Force, Tactile, etc., Introduction to Cameras, Camera calibration, Geometry of Image formation, Euclidean/Similarity/Affine/Projective transformations, Vision applications in robotics.

7. Robot Actuation Systems: Actuators: Electric, Hydraulic, and Pneumatic; Transmission: Gears, Timing Belts and Bearings, Parameters for selection of actuators.

8. Robot Control: Decoupling of nonlinear systems, feedforward and feedback control, control models and strategies, position control and simple feedback synthesis, adaptive control and force control

9. Control Hardware and Interfacing: Embedded systems: Microcontroller Architecture and integration with sensors, actuators, components, Programming Applications for Industrial robot - programming in – VAL II

10. Robot Programming: Motion-oriented and task-oriented languages, Robot application in typical operations and tasks, Mobile robots kinematics, path planning, and control, Research, and the future of robotics.

11. AI in Robotics: Applications in unmanned systems, defense, medical, industries, etc.

12. Application of Robotics: Robotics and Automation for Industry, Robot safety, and social robotics.

Course Learning Outcomes (CLOs):

CLO1: Able to explore the history of robotics, its importance, recent development in this sector, and modern production.

CLO2: Able to apply the knowledge of physics and mathematics involved in the design, construction, and control of robots, with a focus on linear algebra and geometry.

CLO3: Competent to find out the fundamental concepts of electrical and mechanical engineering and their tools that will help them better understand the design and development challenges in the field of robotics.

CLO4: Competent to perform an engineering design task that sharpens analytical, planning, presentation, and teamwork skills.

CLO5: Able to develop and deepen the programming concepts related to robotics.

References:

Learning Materials:

Textbooks:

1. Bruno Siciliano and OussamaKhatib, Springer Handbook of Robotics, Published by Springer, 2008.

2. Roland Siegwart, Illah Reza Nourbakhsh, and DavideScaramuzza, Introduction to Autonomous Mobile Robots, Published by The MIT Press, 2011

3. Robotic Engineering : An Integrated Approach” by Chmielewski and Klafter

4. “Robotics for Engineers” by Y Koren

5. “Introduction to Robotics” by J J Craig

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 4173-0611

Course Title: IT Entrepreneurship Development

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course will prepare the students with the proper knowledge about the background information of support systems, skill sets, financial and risk-covering institutions, and other relevant things to build an enterprise with proper and right decisions. This course is important for IT Entrepreneurship because without proper knowledge of the development process an enterprise can fail within a very short time. Students will learn from this course about the fundamentals and important information to build a successful IT Entrepreneurship.

Course Contents:

1. Introduction: Introduction to Entrepreneurship, Management and Its Evolution, Roles of an Entrepreneur.

2. Entrepreneurial Management: Idea Generation, Screening, Selection, and Managing Resources, Leading and Building the Team in an Enterprise, Strategic Planning, Forms of Ownership, Franchising- From of Business Ownership, Financing Entrepreneurial Ventures, Managing Growth, Expansion and Winding up of business, Valuation of New Company, Corporate Entrepreneurship, Environment, and Strategy.

3. Entrepreneurship, Creativity, and Innovation: Center of Innovation, Incubation, and Entrepreneurship- An expert Interview, Role of Stimulating Creativity, Creative Teams and Managerial Responsibilities, Sources of Innovation, Creativity, and Innovation in IT StartUps.

4. IT Entrepreneurship: Introduction to IT Entrepreneurship, Financing and Risks in IT enterprises, Business Strategies and Scaling Up, Conflict and Conflict Resolution in Firm, Managing Leadership, Succession Planning.

5. Financing The Entrepreneurial Business: Arrangement of funds, Exercise on Writing of Project Report, Financing and Risk, Appraisal of Loans by Financial Institutions, Role of Commercial Banks, Venture Capital, Field Research on IT Entrepreneurship.

Course Learning Outcomes (CLOs):

CLO1: Learn the fundamentals of IT Entrepreneurship.

CLO2: Able to analyze finance and risks of IT Entrepreneurship.

CLO3: Competent to make the right decision as an Entrepreneur.

CLO4: Able to manage different real-world situations of IT Entrepreneurship ethically from the knowledge of this course.

References:

Learning Materials:

Textbooks:

1. Rachid Benlamri & Michael Sparer, Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy: Proceedings, Publisher: Springer

2. Morrill, Richard L., Strategic Leadership

Other Learning Materials: Journals, Web Materials, etc.

Course Title: IT Entrepreneurship Development

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course will prepare the students with the proper knowledge about the background information of support systems, skill sets, financial and risk-covering institutions, and other relevant things to build an enterprise with proper and right decisions. This course is important for IT Entrepreneurship because without proper knowledge of the development process an enterprise can fail within a very short time. Students will learn from this course about the fundamentals and important information to build a successful IT Entrepreneurship.

Course Contents:

1. Introduction: Introduction to Entrepreneurship, Management and Its Evolution, Roles of an Entrepreneur.

2. Entrepreneurial Management: Idea Generation, Screening, Selection, and Managing Resources, Leading and Building the Team in an Enterprise, Strategic Planning, Forms of Ownership, Franchising- From of Business Ownership, Financing Entrepreneurial Ventures, Managing Growth, Expansion and Winding up of business, Valuation of New Company, Corporate Entrepreneurship, Environment, and Strategy.

3. Entrepreneurship, Creativity, and Innovation: Center of Innovation, Incubation, and Entrepreneurship- An expert Interview, Role of Stimulating Creativity, Creative Teams and Managerial Responsibilities, Sources of Innovation, Creativity, and Innovation in IT StartUps.

4. IT Entrepreneurship: Introduction to IT Entrepreneurship, Financing and Risks in IT enterprises, Business Strategies and Scaling Up, Conflict and Conflict Resolution in Firm, Managing Leadership, Succession Planning.

5. Financing The Entrepreneurial Business: Arrangement of funds, Exercise on Writing of Project Report, Financing and Risk, Appraisal of Loans by Financial Institutions, Role of Commercial Banks, Venture Capital, Field Research on IT Entrepreneurship.

Course Learning Outcomes (CLOs):

CLO1: Learn the fundamentals of IT Entrepreneurship.

CLO2: Able to analyze finance and risks of IT Entrepreneurship.

CLO3: Competent to make the right decision as an Entrepreneur.

CLO4: Able to manage different real-world situations of IT Entrepreneurship ethically from the knowledge of this course.

References:

Learning Materials:

Textbooks:

1. Rachid Benlamri & Michael Sparer, Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy: Proceedings, Publisher: Springer

2. Morrill, Richard L., Strategic Leadership

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 4277-0612

Course Title: Network and Server Administration

Course Type: Theory

Pre-requisite: N/A

Credits:3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

Students will get familiar with the fundamental ideas and practices behind networking and system administration via the study of this course. This course offers students the basic theory, concepts, and hands-on experience necessary to design, install, and configure personal computers, peer-to-peer networks, and client-server networks suitable for their individual needs.

Course Contents:

1. Aspects of computer communications from a theoretical standpoint: Networking overview, IP addressing basics.

2. The function of the Computer network: network planning, DHCP, DNS, FTP, HTTP, etc.

3. The architecture of computer networks: implementing and managing WINS, securing network traffic, remote access, and Internet authentication service.

4. Software used in computer networks to manage systems: routing, naming, configuring file services, configuring and monitoring print services, maintaining and updating Windows,

5. The establishment and upkeep of computer networks: maintaining network health with network access protection and IPSec, securing data transmissions and authentication, maintaining file and print services, routine system maintenance, Internet connectivity, system optimization, troubleshooting, and scripting languages.

Course Learning Outcomes (CLOs):

CLO1: able to create and configure peer-to-peer networks for resource sharing.

CLO2: can analyze the needs and create a network architecture for a specific situation.

CLO3: Create and configure IP addressing schemes for a specific situation.

CLO4: For specific situations, will be able to design and configure a client-server network as well as the appropriate network services.

References:

Learning Materials:

Textbooks:

1. Thomas Limoncelli, Christina Hogan and Strata Chalup, The Practice of System and Network Administration, published by Addison-Wesley Professional.

2. AnandaDeveriva, Network Administrators Survival Guide, published by Cisco Press.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Network and Server Administration

Course Type: Theory

Pre-requisite: N/A

Credits:3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

Students will get familiar with the fundamental ideas and practices behind networking and system administration via the study of this course. This course offers students the basic theory, concepts, and hands-on experience necessary to design, install, and configure personal computers, peer-to-peer networks, and client-server networks suitable for their individual needs.

Course Contents:

1. Aspects of computer communications from a theoretical standpoint: Networking overview, IP addressing basics.

2. The function of the Computer network: network planning, DHCP, DNS, FTP, HTTP, etc.

3. The architecture of computer networks: implementing and managing WINS, securing network traffic, remote access, and Internet authentication service.

4. Software used in computer networks to manage systems: routing, naming, configuring file services, configuring and monitoring print services, maintaining and updating Windows,

5. The establishment and upkeep of computer networks: maintaining network health with network access protection and IPSec, securing data transmissions and authentication, maintaining file and print services, routine system maintenance, Internet connectivity, system optimization, troubleshooting, and scripting languages.

Course Learning Outcomes (CLOs):

CLO1: able to create and configure peer-to-peer networks for resource sharing.

CLO2: can analyze the needs and create a network architecture for a specific situation.

CLO3: Create and configure IP addressing schemes for a specific situation.

CLO4: For specific situations, will be able to design and configure a client-server network as well as the appropriate network services.

References:

Learning Materials:

Textbooks:

1. Thomas Limoncelli, Christina Hogan and Strata Chalup, The Practice of System and Network Administration, published by Addison-Wesley Professional.

2. AnandaDeveriva, Network Administrators Survival Guide, published by Cisco Press.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 4278-0612

Course Title: Network and Server Administration Lab

Course Type: Lab

Pre-requisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course will offer students with the knowledge and abilities necessary to set up, operate, and administer a network on server computers that are part of a domain. This course examines network management from both the operating system and hardware perspectives, and it lays the framework for the accompanying Cisco certification.

Course Contents:

Concepts on installation and administration. Configuration and diagnosing issues with devices and resource access. System performance, dependability, and availability will be managed, monitored, and optimized. Design issues and support in an enterprise setting. Troubleshooting and support for end users.

Lab tasks:

➢ Setup of operating system LINUX

➢ Performing the installation of the Windows operating system

➢ Setup of office productivity software such as Microsoft Office or Open Office

➢ Administration of Users and Directories

➢ create scripts for starting up and shutting down an application

➢ Demonstrate the directives for process management and how they are carried out

➢ Enable or disable the root login on the SSH server running CentOS or Ubuntu.

➢ Installation and Configuration of Servers (CentOS and Ubuntu) for Telnet, FTP, Samba, and HTTP

➢ Setting up the Proxy Server Configuration

➢ Setup of the Firewall in Both Windows and Linux

Course Learning Outcomes (CLOs):

CLO1: able to install or upgrade a network operating system while gaining hands-on experience installing Windows Server and setting up Web servers and terminal services

CLO2: competent to configure physical devices, as well as implementing, administering, and monitoring a Windows-based LAN

CLO3: Can evaluate troubleshooting alternatives.

Course Title: Network and Server Administration Lab

Course Type: Lab

Pre-requisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course will offer students with the knowledge and abilities necessary to set up, operate, and administer a network on server computers that are part of a domain. This course examines network management from both the operating system and hardware perspectives, and it lays the framework for the accompanying Cisco certification.

Course Contents:

Concepts on installation and administration. Configuration and diagnosing issues with devices and resource access. System performance, dependability, and availability will be managed, monitored, and optimized. Design issues and support in an enterprise setting. Troubleshooting and support for end users.

Lab tasks:

➢ Setup of operating system LINUX

➢ Performing the installation of the Windows operating system

➢ Setup of office productivity software such as Microsoft Office or Open Office

➢ Administration of Users and Directories

➢ create scripts for starting up and shutting down an application

➢ Demonstrate the directives for process management and how they are carried out

➢ Enable or disable the root login on the SSH server running CentOS or Ubuntu.

➢ Installation and Configuration of Servers (CentOS and Ubuntu) for Telnet, FTP, Samba, and HTTP

➢ Setting up the Proxy Server Configuration

➢ Setup of the Firewall in Both Windows and Linux

Course Learning Outcomes (CLOs):

CLO1: able to install or upgrade a network operating system while gaining hands-on experience installing Windows Server and setting up Web servers and terminal services

CLO2: competent to configure physical devices, as well as implementing, administering, and monitoring a Windows-based LAN

CLO3: Can evaluate troubleshooting alternatives.

Course Code: CSE 4227-0613

Course Title: Computer Graphics

Course Type: Theory

prerequisite: CSE 1201

Credits: 3

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course inspires students to focus on the principles of computer graphics and tackles the knowledge and skills required by computing professionals in computer graphics development. Also improve their capacity to rapidly conceptualize, develop, and modify many sorts of shapes, structures, and images on an interactive basis, which is essential in the field of engineering and imaging technology.

Course Contents:

1. Introduction: Application areas of Computer Graphics, an overview of graphics systems, Video-display devices, Raster - scan systems, Random scan systems, Liquid Crystal Display (LCD), graphics monitors and workstations, and input devices.

2. Output primitives: Points and lines, Line drawing algorithms, Digital Differential Analyser (DDA), Bresenham’s Line-Drawing Algorithm, Bresenham’s Circle Algorithm, Ellipse Generating Algorithm, Mid-point circle, and ellipse algorithms.

3. Filled area primitives: Clipping and Viewport, Flood Fill Algorithm, Boundary Fill Algorithm, Scan-Line Polygon Fill Algorithm.

4. 2D Transformations: Introduction of Transformation, Translation, Scaling, Rotation, Reflection, Shearing, Matrix Representation, Homogeneous Coordinates, Composite Transformation, and Pivot Point Rotation.

5. 2D-Viewing: The Viewing Pipeline, Viewing Coordinate Reference Frame, Window to Viewport Coordinate Transformation, and 2-D Viewing Functions.

6. Clipping Techniques: Clipping, Point Clipping, Line Clipping, Midpoint Subdivision Algorithm, Text Clipping, Polygon, Sutherland-Hodgeman Polygon Clipping, Weiler-Atherton Polygon Clipping.

7. 3-D Geometric transformations: Translation, rotation, scaling, reflection and shear transformations, composite transformations.

8. 3-D viewing: Viewing pipeline, viewing coordinates, view volume, and general projection transforms and clipping.

9. Computer animation: Design of animation sequence, general computer animation functions, raster animation, computer animation languages, key frame systems, and motion specifications.

Course Learning Outcomes (CLOs):

CLO1: Able to explain the applications, areas, graphic pipeline, display, and hardcopy technologies.

CLO2: Able to demonstrate effective OpenGL application programming Interface and apply it for 2D & 3D computer graphics.

CLO3: Able to analyze and apply clipping algorithms and transformation on 2D images.

CLO4: Able to solve the problems on viewing transformations and explain the projection and hidden surface removal algorithms.

CLO5: Able to implement basic ray tracing algorithm, shading, shadows, curves, and surfaces and also solve the problems of curves.

References:

Learning Materials:

Textbooks:

1. Fundamentals of Computer Graphics, Peter Shirley and Steve Marschner, Third Edition. (A.K.Peters Publication house)

2. Schaum’s Outline of Theory and Problems of Computer Graphics, Roy A. Plastock, and Gordon Kalley, published by McGraw-Hill, 2nd Edition.

3. Computer Graphics – Principles and Practice, J. D. Foley, A. Van Dam, S. K. Feiner and J. F. Hughes, Second Edition in C, Pearson Education.

4. Computer Graphics with OpenGL, Donald D. Hearn, M. Pauline Baker, Warren Carithers, Fourth Edition, Pearson Education.

Other Learning Materials: Journals, Web Materials, etc.

Course Title: Computer Graphics

Course Type: Theory

prerequisite: CSE 1201

Credits: 3

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course inspires students to focus on the principles of computer graphics and tackles the knowledge and skills required by computing professionals in computer graphics development. Also improve their capacity to rapidly conceptualize, develop, and modify many sorts of shapes, structures, and images on an interactive basis, which is essential in the field of engineering and imaging technology.

Course Contents:

1. Introduction: Application areas of Computer Graphics, an overview of graphics systems, Video-display devices, Raster - scan systems, Random scan systems, Liquid Crystal Display (LCD), graphics monitors and workstations, and input devices.

2. Output primitives: Points and lines, Line drawing algorithms, Digital Differential Analyser (DDA), Bresenham’s Line-Drawing Algorithm, Bresenham’s Circle Algorithm, Ellipse Generating Algorithm, Mid-point circle, and ellipse algorithms.

3. Filled area primitives: Clipping and Viewport, Flood Fill Algorithm, Boundary Fill Algorithm, Scan-Line Polygon Fill Algorithm.

4. 2D Transformations: Introduction of Transformation, Translation, Scaling, Rotation, Reflection, Shearing, Matrix Representation, Homogeneous Coordinates, Composite Transformation, and Pivot Point Rotation.

5. 2D-Viewing: The Viewing Pipeline, Viewing Coordinate Reference Frame, Window to Viewport Coordinate Transformation, and 2-D Viewing Functions.

6. Clipping Techniques: Clipping, Point Clipping, Line Clipping, Midpoint Subdivision Algorithm, Text Clipping, Polygon, Sutherland-Hodgeman Polygon Clipping, Weiler-Atherton Polygon Clipping.

7. 3-D Geometric transformations: Translation, rotation, scaling, reflection and shear transformations, composite transformations.

8. 3-D viewing: Viewing pipeline, viewing coordinates, view volume, and general projection transforms and clipping.

9. Computer animation: Design of animation sequence, general computer animation functions, raster animation, computer animation languages, key frame systems, and motion specifications.

Course Learning Outcomes (CLOs):

CLO1: Able to explain the applications, areas, graphic pipeline, display, and hardcopy technologies.

CLO2: Able to demonstrate effective OpenGL application programming Interface and apply it for 2D & 3D computer graphics.

CLO3: Able to analyze and apply clipping algorithms and transformation on 2D images.

CLO4: Able to solve the problems on viewing transformations and explain the projection and hidden surface removal algorithms.

CLO5: Able to implement basic ray tracing algorithm, shading, shadows, curves, and surfaces and also solve the problems of curves.

References:

Learning Materials:

Textbooks:

1. Fundamentals of Computer Graphics, Peter Shirley and Steve Marschner, Third Edition. (A.K.Peters Publication house)

2. Schaum’s Outline of Theory and Problems of Computer Graphics, Roy A. Plastock, and Gordon Kalley, published by McGraw-Hill, 2nd Edition.

3. Computer Graphics – Principles and Practice, J. D. Foley, A. Van Dam, S. K. Feiner and J. F. Hughes, Second Edition in C, Pearson Education.

4. Computer Graphics with OpenGL, Donald D. Hearn, M. Pauline Baker, Warren Carithers, Fourth Edition, Pearson Education.

Other Learning Materials: Journals, Web Materials, etc.

Course Code: CSE 4228-0613

Course Title: Computer Graphics Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course encourages students to create and change 2D and 3D visualization and transformations of any geometric object using a graphics library, as well as work with texturing, lighting, and coloring of such things to create many sorts of digital images with diverse effects.

List of Experiments:

➢ Study of basic graphics functions defined in “graphics. h”.

➢ Write a program to draw a Hut or other geometrical figures.

➢ Write a program to draw a line using Bresenhem’s algorithm.

➢ Implement Bresenham’s line drawing algorithm for all types of slopes.

➢ Write a program to draw a line using the DDA algorithm.

➢ Write a program to draw a line using the Mid-Point algorithm.

➢ Write a Program to control a ball using arrow keys.

➢ Create and rotate a triangle about the origin and a fixed point.

➢ Draw a color cube and spin it using OpenGL transformation matrices.

➢ Draw a color cube and allow the user to move the camera suitably to experiment with perspective viewing.

➢ Clip a line using the Cohen-Sutherland algorithm

➢ To draw a simple shaded scene consisting of a teapot on a table. Define suitably the position and properties of the light source along with the properties of the surfaces of the solid object used in the scene.

➢ Design, develop, and implement recursively subdivide tetrahedron to form a 3D Sierpinski gasket. The number of recursive steps is to be specified by the user.

➢ Develop a menu-driven program to animate a flag using the Bezier Curve algorithm.

➢ Develop a menu-driven program to fill the polygon using a scan line algorithm

➢ Write a Program to implement Digital Clock.

➢ Write a Program to make a puzzle game.

➢ Program to draw Sine, Cosine, and Tangent Curves

Course Learning Outcomes (CLOs):

CLO1: Able to demonstrate effective OpenGL programs to solve graphics programming problems involving various shapes.

CLO2: Able to implement DDA, Bresenham's, and Mid Point Algorithm to implement the Line Drawing Algorithm.

CLO3: Able to implement 2D and 3D transformation.

CLO4: Able to develop design and problem-solving skills with application to computer graphics.

CLO5: Able to implement color, modeling, shading, and animation.

Course Title: Computer Graphics Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 1

Rationale:

This course encourages students to create and change 2D and 3D visualization and transformations of any geometric object using a graphics library, as well as work with texturing, lighting, and coloring of such things to create many sorts of digital images with diverse effects.

List of Experiments:

➢ Study of basic graphics functions defined in “graphics. h”.

➢ Write a program to draw a Hut or other geometrical figures.

➢ Write a program to draw a line using Bresenhem’s algorithm.

➢ Implement Bresenham’s line drawing algorithm for all types of slopes.

➢ Write a program to draw a line using the DDA algorithm.

➢ Write a program to draw a line using the Mid-Point algorithm.

➢ Write a Program to control a ball using arrow keys.

➢ Create and rotate a triangle about the origin and a fixed point.

➢ Draw a color cube and spin it using OpenGL transformation matrices.

➢ Draw a color cube and allow the user to move the camera suitably to experiment with perspective viewing.

➢ Clip a line using the Cohen-Sutherland algorithm

➢ To draw a simple shaded scene consisting of a teapot on a table. Define suitably the position and properties of the light source along with the properties of the surfaces of the solid object used in the scene.

➢ Design, develop, and implement recursively subdivide tetrahedron to form a 3D Sierpinski gasket. The number of recursive steps is to be specified by the user.

➢ Develop a menu-driven program to animate a flag using the Bezier Curve algorithm.

➢ Develop a menu-driven program to fill the polygon using a scan line algorithm

➢ Write a Program to implement Digital Clock.

➢ Write a Program to make a puzzle game.

➢ Program to draw Sine, Cosine, and Tangent Curves

Course Learning Outcomes (CLOs):

CLO1: Able to demonstrate effective OpenGL programs to solve graphics programming problems involving various shapes.

CLO2: Able to implement DDA, Bresenham's, and Mid Point Algorithm to implement the Line Drawing Algorithm.

CLO3: Able to implement 2D and 3D transformation.

CLO4: Able to develop design and problem-solving skills with application to computer graphics.

CLO5: Able to implement color, modeling, shading, and animation.

Course Code: CSE 4279-0612

Course Title: Wireless Network

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks:

Year/Level: 4

Semester/Term: 2

Rationale:

This course focuses on data and signals transmission through different media. Different wireless techniques, satellite, and cellular telephony, different types of modulation and demodulation, and performance of data transmission with congestion and quality control are discussed here.

Course Outlines:

1. Introduction to wireless networks

2. Data and signal: Transmission impairment, attenuation, distortion, noise,

3. Wireless transmission

4. Frequencies

5. Modulation

6. Demodulation

7. Different types of wireless communication networks

8. Wireless WAN: Frequency-Reuse Principle, Transmitting, Receiving, Roaming, First Generation, Second Generation, Third Generation

9. Cellular Telephone: GSM, IS-95, GSM architecture

10. Satellite Network: Orbits Footprint, Three Categories of Satellites, GEO Satellites, MEO Satellites, LEO Satellites

11. Data rate limit: Noiseless Channel: Nyquist Bit Rate Noisy Channel: Shannon Capacity Using Both Limits

12. Performance: Bandwidth, Throughput, Latency (Delay), Delay Product

13. Congestion control: Data traffic, Traffic descriptor, Loop congestion, Flow characteristics, flow classes

14. Quality service: Quality of service

Course Learning Outcomes (CLOs):

CLO1: Describe and explain different wireless transmission and techniques

CLO2: Able to analyze different data transmission channels, data rate, bandwidth, and delay

CLO3: Able to develop and implement different modulation and demodulation techniques, analyze network traffic and provide solutions

References:

Learning Materials:

Textbooks:

1. Cory Beard and William Stallings, Wireless Communication Networks and Systems, (ISBN: 0133594173, available online).

2. David Tse and Pramod Viswanath, Fundamentals of Wireless Communication [T & V] (available online).

Other Learning Materials: Problem-solving platforms, webinars, Web Materials, etc.

Course Title: Wireless Network

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks:

Year/Level: 4

Semester/Term: 2

Rationale:

This course focuses on data and signals transmission through different media. Different wireless techniques, satellite, and cellular telephony, different types of modulation and demodulation, and performance of data transmission with congestion and quality control are discussed here.

Course Outlines:

1. Introduction to wireless networks

2. Data and signal: Transmission impairment, attenuation, distortion, noise,

3. Wireless transmission

4. Frequencies

5. Modulation

6. Demodulation

7. Different types of wireless communication networks

8. Wireless WAN: Frequency-Reuse Principle, Transmitting, Receiving, Roaming, First Generation, Second Generation, Third Generation

9. Cellular Telephone: GSM, IS-95, GSM architecture

10. Satellite Network: Orbits Footprint, Three Categories of Satellites, GEO Satellites, MEO Satellites, LEO Satellites

11. Data rate limit: Noiseless Channel: Nyquist Bit Rate Noisy Channel: Shannon Capacity Using Both Limits

12. Performance: Bandwidth, Throughput, Latency (Delay), Delay Product

13. Congestion control: Data traffic, Traffic descriptor, Loop congestion, Flow characteristics, flow classes

14. Quality service: Quality of service

Course Learning Outcomes (CLOs):

CLO1: Describe and explain different wireless transmission and techniques

CLO2: Able to analyze different data transmission channels, data rate, bandwidth, and delay

CLO3: Able to develop and implement different modulation and demodulation techniques, analyze network traffic and provide solutions

References:

Learning Materials:

Textbooks:

1. Cory Beard and William Stallings, Wireless Communication Networks and Systems, (ISBN: 0133594173, available online).

2. David Tse and Pramod Viswanath, Fundamentals of Wireless Communication [T & V] (available online).

Other Learning Materials: Problem-solving platforms, webinars, Web Materials, etc.

Course Code: CSE 4280-0612

Course Title: Wireless Network Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course focuses on implementing different modulation, demodulation, and shifting keys using Matlab. Moreover, this will be hands-on learning on wireless communication and in-depth knowledge of Matlab.

Course Outlines:

➢ Introduction to Matlab, Install and Overview

➢ Syntax and library functions of Matlab, problem-solving with Matlab

➢ Plot, subplot, and graphical visualization with Matlab

➢ Frequencies, phase, sin waveform, cos waveform

➢ Amplitude modulation

➢ Phase modulation

➢ Amplitude-shift keying (ASK)

➢ Frequency-shift keying (FSK)

➢ Phase shift keying (PSK)

➢ Demodulation

Course Learning Outcomes (CLOs):

CLO1: Understand and use Matlab software for different types of problem-solving

CLO2: Able to generate different transmission graphs and waveforms using Matlab

CLO3: Able to develop and implement different modulation and demodulation techniques, ASK, FSK, PSK

References:

Learning Materials:

Textbooks:

1. Cory Beard and William Stallings, Wireless Communication Networks and Systems, (ISBN: 0133594173, available online).

2. David Tse and Pramod Viswanath, Fundamentals of Wireless Communication [T & V] (available online).

Other Learning Materials: Problem-solving platforms, webinars, Web Materials, etc.

Course Title: Wireless Network Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course focuses on implementing different modulation, demodulation, and shifting keys using Matlab. Moreover, this will be hands-on learning on wireless communication and in-depth knowledge of Matlab.

Course Outlines:

➢ Introduction to Matlab, Install and Overview

➢ Syntax and library functions of Matlab, problem-solving with Matlab

➢ Plot, subplot, and graphical visualization with Matlab

➢ Frequencies, phase, sin waveform, cos waveform

➢ Amplitude modulation

➢ Phase modulation

➢ Amplitude-shift keying (ASK)

➢ Frequency-shift keying (FSK)

➢ Phase shift keying (PSK)

➢ Demodulation

Course Learning Outcomes (CLOs):

CLO1: Understand and use Matlab software for different types of problem-solving

CLO2: Able to generate different transmission graphs and waveforms using Matlab

CLO3: Able to develop and implement different modulation and demodulation techniques, ASK, FSK, PSK

References:

Learning Materials:

Textbooks:

1. Cory Beard and William Stallings, Wireless Communication Networks and Systems, (ISBN: 0133594173, available online).

2. David Tse and Pramod Viswanath, Fundamentals of Wireless Communication [T & V] (available online).

Other Learning Materials: Problem-solving platforms, webinars, Web Materials, etc.

Course Code: CSE 4281-0613

Course Title: Software Architecture

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course prepares the students with sufficient knowledge and skills which are required to design and document software architectures based on sufficiently detailed requirement specifications for small and medium-sized systems. Students will learn about the analysis and design methods and tools that allow them to solve various types of problems with proper design and methods from the course experience.

Course Contents:

1. Introduction to Software Architecture: introduction to software, Organogram, SDLC Concept, Software Types, and Information Gathering Process.

2. Feasibility Study: Economical, Technical, and Behavioral Study, SWOT Analysis, Cost-Benefit Analysis

3. Diagrams: UML Design, Context Diagram, Activity Diagram, Data Flow Diagram, Use Case Diagram, Mockup Design

4. Deployment: Deployment Diagram, Three Golden Rules

5. SRS: SRS Introduction, Functional and Non-functional Requirements, SRS Design

Course Learning Outcomes (CLOs):

CLO1: Students will learn the basic concept of System Architecture

CLO2: Competent to design a System Architecture.

CLO3: Able to analyze different types of system designs and test their feasibility.

CLO4: Competent to solve real project-related problems related to System Architecture and Design.

References:

Learning Materials:

Textbooks:

1. Elias M. Awad, Systems Analysis and Design, Published by Galgotia Publications Pvt Ltd, 2nd Edition.

2. I. T. Hawryszkiewycz, Introduction to Systems Analysis and Design, Published by Prentice Hall of India, 3rd Edition.

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Title: Software Architecture

Course Type: Theory

prerequisite: N/A

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course prepares the students with sufficient knowledge and skills which are required to design and document software architectures based on sufficiently detailed requirement specifications for small and medium-sized systems. Students will learn about the analysis and design methods and tools that allow them to solve various types of problems with proper design and methods from the course experience.

Course Contents:

1. Introduction to Software Architecture: introduction to software, Organogram, SDLC Concept, Software Types, and Information Gathering Process.

2. Feasibility Study: Economical, Technical, and Behavioral Study, SWOT Analysis, Cost-Benefit Analysis

3. Diagrams: UML Design, Context Diagram, Activity Diagram, Data Flow Diagram, Use Case Diagram, Mockup Design

4. Deployment: Deployment Diagram, Three Golden Rules

5. SRS: SRS Introduction, Functional and Non-functional Requirements, SRS Design

Course Learning Outcomes (CLOs):

CLO1: Students will learn the basic concept of System Architecture

CLO2: Competent to design a System Architecture.

CLO3: Able to analyze different types of system designs and test their feasibility.

CLO4: Competent to solve real project-related problems related to System Architecture and Design.

References:

Learning Materials:

Textbooks:

1. Elias M. Awad, Systems Analysis and Design, Published by Galgotia Publications Pvt Ltd, 2nd Edition.

2. I. T. Hawryszkiewycz, Introduction to Systems Analysis and Design, Published by Prentice Hall of India, 3rd Edition.

Other Learning Materials: Journals, Web Materials, YouTube Videos, etc.

Course Code: CSE 4282-0613

Course Title: Software Architecture Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course prepares the students with sufficient knowledge and skills to develop a System Architecture and implement software from the architecture created by the students. From this course, students will learn about the system development process properly.

Course Contents:

➢ Introduction to the System Architecture

➢ Project Proposal

➢ Presentation on Feasibility Analysis of the proposed project

➢ Presentation on SWOT Analysis of the proposed project

➢ Presentation and review of Benchmark Analysis with the proposed project

➢ Creating UML Diagram and Relational Diagram

➢ Design Activity Diagram

➢ Design a Data Flow Diagram

➢ Design Use-Case Diagram

➢ Design Class Diagram

➢ Project implementation progress review

➢ Learn to use Project Management Tools

➢ Final Project submission and presentation

Course Learning Outcomes (CLOs):

CLO1: Students will learn the practical experience of basic System Architecture design.

CLO2: Competent to design an ethical System Architecture with software.

CLO3: Able to implement a System with a proper System Architecture and solve complex engineering problems by working as a team through adequate management.

References:

Learning Materials:

Textbooks:

1. Elias M. Awad, Systems Analysis and Design, Published by Galgotia Publications Pvt Ltd, 2nd Edition.

2. I. T. Hawryszkiewycz, Introduction to Systems Analysis and Design, Published by Prentice Hall of India, 3rd Edition.

Other Learning Materials: Journals, Web Materials, YouTube Videos etc.

Course Title: Software Architecture Lab

Course Type: Lab

prerequisite: N/A

Credits: 1

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course prepares the students with sufficient knowledge and skills to develop a System Architecture and implement software from the architecture created by the students. From this course, students will learn about the system development process properly.

Course Contents:

➢ Introduction to the System Architecture

➢ Project Proposal

➢ Presentation on Feasibility Analysis of the proposed project

➢ Presentation on SWOT Analysis of the proposed project

➢ Presentation and review of Benchmark Analysis with the proposed project

➢ Creating UML Diagram and Relational Diagram

➢ Design Activity Diagram

➢ Design a Data Flow Diagram

➢ Design Use-Case Diagram

➢ Design Class Diagram

➢ Project implementation progress review

➢ Learn to use Project Management Tools

➢ Final Project submission and presentation

Course Learning Outcomes (CLOs):

CLO1: Students will learn the practical experience of basic System Architecture design.

CLO2: Competent to design an ethical System Architecture with software.

CLO3: Able to implement a System with a proper System Architecture and solve complex engineering problems by working as a team through adequate management.

References:

Learning Materials:

Textbooks:

1. Elias M. Awad, Systems Analysis and Design, Published by Galgotia Publications Pvt Ltd, 2nd Edition.

2. I. T. Hawryszkiewycz, Introduction to Systems Analysis and Design, Published by Prentice Hall of India, 3rd Edition.

Other Learning Materials: Journals, Web Materials, YouTube Videos etc.

Course Code: CSE 4283-0612

Course Title: Distributed Database Management Systems

Course Type: Theory

prerequisite: DBMS

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course encourages students to optimize basic distributed database transactions, query processing, concurrency control, and other distributed database system functions using advanced features that include complex data, as well as evaluate various distributed database models and designs in order to contribute to modern database systems.

Course Contents:

1. Introduction: What is DDBMS? Distributed data processing; Problem regions; DDBS advantages and downsides A brief introduction to database and computer network principles.

2. Architectures: Transparencies in a distributed database management system; architecture of a distributed database management system; global directory concerns.

3. Design: Fragmentation, Data allocation, Alternative design methodologies, Distributed design concerns.

4. Data control: Semantic Integrity Control; View management; Data security

5. Query Processing: Query processing objectives, query processor characteristics, query processing layers, query decomposition Data distribution localization.

6. Query Optimization: Factors that influence query optimization; centralized query optimization; fragment query ordering; Algorithms for query optimization that are distributed.

7. Transaction management: The transaction idea; Transaction Management Goals; Transaction Characteristics; Transaction Taxonomy.

8. Concurrency control: Deadlock management; Concurrency control in centralized database systems; Concurrency control in DDBSs; Distributed concurrency control techniques;

9. Reliability: Issues with DDBS reliability; Failure types; Reliability approaches; Commit processes; Recovery Protocols

10. Parallel database systems: Load balancing; parallel architectures; parallel query processing and optimization

11. Others: Multi-databases, Mobile Databases, Distributed Object Management

Course Learning Outcomes (CLOs):

CLO1: Explain and analyze the basic theories and needs that impact distributed database system design.

CLO2: Examine and implement distributed database functions and packages that are appropriate for enterprise database creation and maintenance.

CLO3: Analyze and compare different distributed database and data warehouse designs and architectures.

CLO4: Examine and compare strategies for storing, managing, and analyzing large amounts of data.

References:

Learning Materials:

Textbooks:

1. Distributed Systems: Principles and Paradigms by Andrew S. Tanenbaum and Maarten Van Steen

2. Distributed Database Management Systems: A Practical Approach by Saeed K. Rahimi and Frank S. Haug

3. Distributed Systems: Concepts and Design by George Coulouris, Jean Dollimore, Tim Kinberg, and Gordon Blair

4. Principles of Distributed Database Systems by M. Tamer Ozsu and Patrick Valduriez

Course Title: Distributed Database Management Systems

Course Type: Theory

prerequisite: DBMS

Credits: 3

Contact Hours: 42

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course encourages students to optimize basic distributed database transactions, query processing, concurrency control, and other distributed database system functions using advanced features that include complex data, as well as evaluate various distributed database models and designs in order to contribute to modern database systems.

Course Contents:

1. Introduction: What is DDBMS? Distributed data processing; Problem regions; DDBS advantages and downsides A brief introduction to database and computer network principles.

2. Architectures: Transparencies in a distributed database management system; architecture of a distributed database management system; global directory concerns.

3. Design: Fragmentation, Data allocation, Alternative design methodologies, Distributed design concerns.

4. Data control: Semantic Integrity Control; View management; Data security

5. Query Processing: Query processing objectives, query processor characteristics, query processing layers, query decomposition Data distribution localization.

6. Query Optimization: Factors that influence query optimization; centralized query optimization; fragment query ordering; Algorithms for query optimization that are distributed.

7. Transaction management: The transaction idea; Transaction Management Goals; Transaction Characteristics; Transaction Taxonomy.

8. Concurrency control: Deadlock management; Concurrency control in centralized database systems; Concurrency control in DDBSs; Distributed concurrency control techniques;

9. Reliability: Issues with DDBS reliability; Failure types; Reliability approaches; Commit processes; Recovery Protocols

10. Parallel database systems: Load balancing; parallel architectures; parallel query processing and optimization

11. Others: Multi-databases, Mobile Databases, Distributed Object Management

Course Learning Outcomes (CLOs):

CLO1: Explain and analyze the basic theories and needs that impact distributed database system design.

CLO2: Examine and implement distributed database functions and packages that are appropriate for enterprise database creation and maintenance.

CLO3: Analyze and compare different distributed database and data warehouse designs and architectures.

CLO4: Examine and compare strategies for storing, managing, and analyzing large amounts of data.

References:

Learning Materials:

Textbooks:

1. Distributed Systems: Principles and Paradigms by Andrew S. Tanenbaum and Maarten Van Steen

2. Distributed Database Management Systems: A Practical Approach by Saeed K. Rahimi and Frank S. Haug

3. Distributed Systems: Concepts and Design by George Coulouris, Jean Dollimore, Tim Kinberg, and Gordon Blair

4. Principles of Distributed Database Systems by M. Tamer Ozsu and Patrick Valduriez

Course Code: CSE 4284-0612

Course Title: Distributed Database Management Systems Lab

Course Type: Lab

prerequisite: DBMS

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course motivates students to design and develop complex projects using distributed database functions and queries based on advanced models - distributed databases to solve real-life problems.

Lab Contents:

➢ Introduction to the distributed database management system

➢ Analysis and Design of a sample distributed database system

➢ Distributed database design for any store management system

➢ Implement a Deadlock Detection Algorithm for the distributed database using wait for graph

➢ Object Oriented Database – Extended Entity Relationship (EER) model for University Database

➢ Parallel Database – Implementation of Parallel Join & Parallel Sort Algorithm

➢ Active Database Design and Implementation using Triggers & Assertions for an organizational database.

➢ Deductive Database – Constructing Knowledge Database for Kinship Domain (Family Relations)

➢ Study and Working on the WEKA Tool

➢ Query Processing – Implementation of an Efficient Query Optimizer

➢ Designing XML Schema for Company Database

Course Learning Outcomes (CLOs):

CLO1: Students are able to understand the steps of query processing, and optimization techniques are applied to Distributed databases.

CLO2: Able to understand Transaction management and compare various approaches to concurrency control in Distributed Databases.

CLO3: Able to apply various algorithms and techniques for deadlock and recovery in Distributed databases.

Course Title: Distributed Database Management Systems Lab

Course Type: Lab

prerequisite: DBMS

Credits: 1

Contact Hours: 60

Total Marks: 100

Year/Level: 4

Semester/Term: 2

Rationale:

This course motivates students to design and develop complex projects using distributed database functions and queries based on advanced models - distributed databases to solve real-life problems.

Lab Contents:

➢ Introduction to the distributed database management system

➢ Analysis and Design of a sample distributed database system

➢ Distributed database design for any store management system

➢ Implement a Deadlock Detection Algorithm for the distributed database using wait for graph

➢ Object Oriented Database – Extended Entity Relationship (EER) model for University Database

➢ Parallel Database – Implementation of Parallel Join & Parallel Sort Algorithm

➢ Active Database Design and Implementation using Triggers & Assertions for an organizational database.

➢ Deductive Database – Constructing Knowledge Database for Kinship Domain (Family Relations)

➢ Study and Working on the WEKA Tool

➢ Query Processing – Implementation of an Efficient Query Optimizer

➢ Designing XML Schema for Company Database

Course Learning Outcomes (CLOs):

CLO1: Students are able to understand the steps of query processing, and optimization techniques are applied to Distributed databases.

CLO2: Able to understand Transaction management and compare various approaches to concurrency control in Distributed Databases.

CLO3: Able to apply various algorithms and techniques for deadlock and recovery in Distributed databases.

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