University of Scholars | +88 01844 075 476 | 40, Kemal Ataturk Ave, Banani, Dhaka-1213

CSE Course Description

  • Home
  • CSE Course Description
Image

 Details of the Offered Courses

 B.Sc. in Computer Science & Engineering 

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 library and user defined functions. Also, it helps to develop basic programming and problem-solving skills to program design and development.                                                                                                                                               

Course Contents:

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

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

Keywords and library functions: Uses of all keywords, description and code examples

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

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

Function: Declaration, return type, argument, pointer argument

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

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

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

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

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

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

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 of problems of contemporary technologies.

References:

Learning Materials

SL No.

Text Books

Others Learning Materials

1

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

Journals, Web Materials,  etc.

2

Teach yourself c by herbert schildt

3

Competitive Programmer’s Handbook, Antti Laaksonen

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, 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, mechanisms and solve problems using structured programming language.
CLO3: Develop basic programming skills with respect to program design and development.

References:

Learning Materials

SL No.

Text Books

Others Learning Materials

1

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

Journals, Web Materials, etc.

2

Teach yourself c by Herbert Schildt

3

Competitive Programmer’s Handbook, Antti Laaksonen

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 the unifying link across interdisciplinary studies.

Course Contents:

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

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

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

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, Effect of structure on acid bases properties. 

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.

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.

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

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 rate of reaction. Theories of chemical reaction rate, Activation Energy, Activation complex etc. 

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

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

References:

Learning Materials

SL No.

Text Books

Others Learning Materials

1.

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

Journals, Web Materials, etc.

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.

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 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 group 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 different solution (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 formation of geometrical configurations.  This course is designed to provide theoretical knowledge regarding limit and continuity, differentiations, extreme values, integrations, geometrical configurations in two and three dimensions like straight lines, circles, planes, spheres and cylinders.

Course Contents:

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.

Expansions of functions:

Rolle's theorem, Mean value theorem, Taylor's and Maclaurin’s theorems.

Indefinite and definite integrals:

Fundamental of integrations, Indefinite integral by different methods, Definite integrals and its properties; Walli’s formula, Reduction theorem, Multiple Integrals.

Improper Integrals, Infinite integrals, Gamma and Beta function, Improper integral of first kind and second kinds Multiple Integrals.

Applications of proper and improper integrals:

Determination of Area, Are lengths, volume of solids of revolutions, Intrinsic equation in Cartesian and polar coordinate.

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.

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 fundamentals of differential and integral calculus, and co-ordinate geometry.
CLO2: Analyze and sketch function, lines, circles, Parabola, ellipse, planes and spheres.
CLO3: Compute rate of changes of functions, 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

SL 

No.

Text Books

Others Learning  Materials

1

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

Journals, Web Materials,  YouTube Videos etc.

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

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:

Waves and oscillations: Differential equation of simple harmonic oscillator, total energy and average energy, 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.

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.

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

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

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

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

Velocity of Sound and Vibration: Velocity of longitudinal waves in a gaseous medium, velocity of sound in liquids, 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, intensity of sound, limits of audibility, architectural acoustics.

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

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

Surface tension: Surface tension as a molecular phenomenon.

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 kinetic theory of gases, theories of light, sound, fluid mechanics and thermodynamics. 

References: 

SL 

No.

Text Books

Others Learning Materials

1

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

Journals, Website Materials, 

YouTube Videos etc.

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

course module.

2

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

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

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 the observation and calculation. Students will acquire a 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 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 given spiral spring.
  6. Investigate the characteristics of series DC circuits and to 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 the Young’s modulus of the given material bar by non-uniform bending using pin and microscope method.
  9. Determination of the moment of inertia of a given disc using 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 team work.
CLO3: Able to understand measurement technologies, usage of lab instruments and real time applications of Physics in engineering studies.

References:

Learning Materials

SL No.

Text Books

Others Learning Materials

1

David M. Loyd, Physics Laboratory Manual, Third Edition

Journals, Web Materials, etc.

2

Physics 103A Laboratory Manual 10th Edition

Course Code: HRM 1103 - 0413

 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 on 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, concept of risk and return related to financial decisions, introduction to financial institutions, investments, and corporate finance. 

Course Contents:

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.

Foundations of individual behavior:  Intellectual ability, physical ability, Biographical Characteristics, Difference 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

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.

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, 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.

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.

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.

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

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

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.

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

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

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

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 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 in team to disseminate information and propose solutions to maximize shareholders wealth and company’s profit.

References: 

SL 

No.

Text Books

Others Learning Materials

1

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

Journals, Website Materials, YouTube Videos etc.

2

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

3

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

4

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

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 current politics and economy of the country. This course will deepen students' understanding of complex interconnection of historical events which lead to the formation of Bangladesh, 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 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 on 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:

Text Books

Reference Books

Learning Materials

Bangladesh Studies, MD

Hasibur Rahman

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

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 Content:

  • 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 full stop, comma, colon, semicolon, apostrophe, capital letter, 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, 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 adapt different techniques of reading academic and non-academic   textbooks.
CLO2: Adapt different techniques of listening to academic and non- academic conversation.
CLO3: Develop confidence in initiating a conversation in the target language.
CLO4: Develop willingness to establish social communication. 
CLO5: Start generating ideas on an academic topic by thinking critically and ethically.

References:

SL 

No.

Text Books

Others Learning Materials

1

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

Journals, Website Materials, YouTube Videos etc.

2

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

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:

Linear Algebra:  Solution of the system of linear equations, Determinant, Matrix, Rank and nullity of 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.

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

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.

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

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 solution of system of linear equations, matrices, eigenvalues and eigenvectors, complex function, singularities, differentiation and integration.
CLO4: Apply acquired knowledge in solving problems arises in engineering applications.
CLO5: Develop algorithms and software relating to engineering applications.

References:

Learning Materials

SL No.

Text Books

Others Learning Materials

1

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

Journals, Web Materials, YouTube Videos etc.

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.

 Rationale:

Object Oriented Programming (OOP) is a programming architecture which 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:

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

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 

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

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

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.

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

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

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

Course Learning Outcomes (CLOs)

CLO1: Students will be able to understand the basics 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 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

SL No.

Text Books

Others Learning Materials

1

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

Journals, Web Materials, etc.

2

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

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 Mark

s: 100 

Year/Level:  2                   

Semester/Term: 1 

Rationale:  

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

Lab Tasks: 

Setup Java environment, Introduction to Java and visualization of Main() Method.  

Exploring the data types of Java 

Create Classes and Objects, Instance 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

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

Journals, Web Materials, etc. 

2 

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

  

  

Course Code: EEE 1211-0714 

Course Title: Electrical Circuit Analysis 

Course Type: Theory      

Prerequisite: PHY-1111-0533 

Credits: 3               

Contact Hours: 42            

Total Marks: 10

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:

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. 

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. 

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 booth DC and AC circuits. 

References   

Learning Materials 

 

Text Books 

Learning Materials 

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

Journals, websites, YouTube videos 

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

 

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

 

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 which 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, peak factor of sinusoidal wave, 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 of using PSpice/Proteus software for electrical circuit studies. 

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

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

References:  

Learning Materials 

 

Text Books 

Learning Materials 

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

Journals, websites, YouTube videos 

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

 

3) PSpice and Proteus software (Updated version). 

 

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, art of problem solving, cryptography, automated theorem proving, and software development. 

Course Contents: 

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

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

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

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

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

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. 

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. 

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

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. 

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

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 developme  

References: 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

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

Journals, Web Materials, etc. 

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.  

 

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, most natural, straightforward, and clear tactics to become a great presenter and public speaker. Art of Presentation will suit to 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: 

  1. Introduction to Power-point Presentation 
  2. Effective Body Language
  3. Purpose of Presentation
  4. Voice Control
  5. Audience Assessment
  6. Presenting Effectively
  7. Choosing Right topic
  8. Audience Involvement
  9.  Rehearsal
  10. Check for Understanding  

CLO1 

Create incredible contents, 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 audience attention right from the start and keeps it. 

References:   

Learning Materials 

 

Text Books 

Learning Materials 

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/B08D762XRVPrinted Version is also available at “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. 

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 formation and solution techniques of differential equations using different methods and Laplace transformation, and Fourier transformations.    

Course Content: 

Ordinary Differential Equations (ODE): Formation of ordinary differential equation, Solutions of first order ordinary differential equations using different methods, Solution of second and higher orders differential equations and its 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. 

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. 

Fourier transformation (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. 

Laplace Transforms (LT):  Laplace transforms of elementary functions and its applications, Inverse Laplace transforms, Laplace transforms of ordinary and Partial differentiations, Solution of differential equations by Laplace transforms, 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 

 

 

 

SL No. 

 

Text Books 

Others Learning Materials 

1 

 

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

Journals, Web Materials, YouTube Videos etc. 

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 

 

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 diode, Bi polar 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 Content:  

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.  

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

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.   

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, analysis of feedback amplifier. 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 wave shaping, Clipping and Clamping circuits, Non-Linear function circuits. Negative resistance switching circuits. Timing circuits; Bi-stable, mono-stable and A stable multi vibrators, Sweep and staircase generator, IC 555 and its application. 

CLO1: Explain the operation principle and terminal characteristics of 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 its 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 use in building up and development of any required circuit. Besides, students will also be able to learn to generate desired output of any electronic circuit.  

Lab Tasks: 

Exp: 01: I-V Characteristics of 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, and 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 the students with a little knowledge of computers.  

Course Contents: 

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

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

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

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

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

MS Office Fundamentals: Introduction of MS Word, MS Excel, MS Power point, 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. 

Security and Networking: Introduction to security and networking, Data and Information, File Sharing, Internet Services, 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 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 the data representation and work with different number systems and certain computer configuration 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

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

Journals, Web Materials, etc. 

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. 

  

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 with 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 Language 
Understand the fundamental concept of Compiler and Interpreter. 
Understand the fundamental concept of Flow Chart and Algorithm. 
Introduction to System Software (Various Operating Systems) 
Introduction to Network, Security System 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 the 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, cyber-crime and ethical issues. 

 

Course Code: CSE 2121–0613  

Course Title: System Analysis and Design 

Course Type: Theory               

Pe- 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:

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

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

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)  

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. 

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 

 

 

SL No. 

Textbooks 

Others Learning Materials 

1 

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

  

Journals, Web Materials, etc. 

2 

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

 

Course Code: CSE 2122-0613 

Course Title: System Analysis and Design Lab 

Course Type: Lab               

Pe- 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 convesion 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, are well-organized, show professionalism, and adhere to conventional business English standards. 

CLO3: Competent to work alongside with and lead teams in a variety of settings. 
CLO4: Able to solve information systems challenges, 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 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

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

Web Materials, etc. 

  

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

  

https://gencor.in/autocad-syllabus/ 

AutoCAD Training Syllabus 

 

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.  

 

 Course Code: CSE 2105-0613 

Course Title: Competitive Programming-I 

Course Type: Lab       

PrerequisiteCSE 1111-0613, CSE 1213-0613Credits: 1               

Contact Hours:         

Total Marks: 100 

Total Marks: 100 

Credits: 1               

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 Content: 

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

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

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

Basic Contest - 01 

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

Basic contest - 02 

Integer array: Array manipulation and operations 

Complexity Analysis: Time complexity, Space complexity, Code optimization 

Functions: Return type, arguments, parameters, pass by references  

Basic Contest - 03 

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

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

Basic Contest- 04 

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, 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 to perform team work, interact with programming solving community, learn strategic planning of problem setting community and style of international standard of problem solving to adapt the new emerging technologies. 

References: 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

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

Problem solving platforms, Webinars, Web Materials,  etc. 

2 

Competitive Programmer’s Handbook, Antti Laaksonen 

 

3 

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

  

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 to 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's 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, 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Business Communication for Success 

Scott McLean 

Journals, Web Materials,  etc.. 

2 

Business Communication Essentials 

Courtland L Bovee, Jean A. Scribner, and John Thill 

  

 

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:  

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, Misuses and abuse of statistics; Sources and types of statistical data, etc. 

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. 

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. 

Statistical measurements:

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

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 correlation. 

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. 

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. 

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 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

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

Journals, Web Materials, YouTube Videos etc. 

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 

 

 

 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 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 also intended to enable the learners to get the 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 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:    

Introduction: 

Data Structure and Algorithm Basics, Characteristics, The need for Analysis, Problem Development Steps, Complexity 

Arrays and Pointer: 

Single and multi-dimensional arrays, analysis of array insert, delete, and search operations both linear and binary search, Pointer 

Linked Lists: 

Analysis of insert, remove, and search operations in single-linked, doubly-linked, and circular lists 

Methodology of Analysis: 

Asymptotic Notation, Best Case, Worst Case, Average Case, Solving Recurrence Equations, 

Single and multi-dimensional arrays, analysis of array insert, delete, and search operations both linear and binary search, Pointer 

Linked Lists: 

Analysis of insert, remove, and search operations in single-linked, doubly-linked, and circular lists 

Methodology of Analysis: 

Asymptotic Notation, Best Case, Worst Case, Average Case, Solving Recurrence Equations, Amortized Analysis 

Asymptotic Analysis: 

Time Complexity, Space Complexity, Asymptotic Notations, Asymptotic Upper Bound, Asymptotic Lower Bound, Asymptotic Tight Bound, O-Notation, ω- Notation 

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. 

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. 

Heaps: 

Introduction to heap as a data structure. analysis of insert, extract-min/max and delete-min/max operations, applications to priority queues. 

 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 

Dynamic Programming:

Fibonacci number series, Knapsack problem, Tower of Hanoi, All pair shortest path by Floyd-Warshall, Shortest path by Dijkstra 

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 

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 Algorithm 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Data Structures – Edward Martin Reingold; Wilfred J. Hansen (2011) 

Journals, Web Materials, YouTube Videos etc. 

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) 

 

Course Code: CSE 2216-0613 

Course Title: Data Structures and Algorithm Lab 

Course Type: Lab          

PrerequisitePrerequisite: 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 structure and algorithms, such as sorting, finding shortest paths, basic data structures to analyze the 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 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 Doubly Linked List using templates. Include functions for insertion, deletion and search of a number, reverse the list.  

Implement Circular Linked List using templates. Include functions for insertion, deletion and search of a number, 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 to compute the factors of a given no. (i)using recursion, (ii) using iteration  

Write a program to display fibonacci series (i)using recursion, (ii) using iteration  

Write a program to calculate GCD of 2 number (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. 

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 additional stack and Queue. 

Write a program to implement different Matrix representations using 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 Greedy Approach by performing Prim’s and Kruskal’s Algorithm.  
Course Learning Outcomes (CLOs) 

CLO1: Able to identify abstract data structures, implement and empirically analyze linear and non-linear data structures and practise 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 team work in mind.  

CLO4: Able to write a program using the optimum data structure or the application at hand and exploit 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: Criminoloty       

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 the 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 the numerical approximation and solution of 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:  

Introduction: Basic Numerical Concepts, Approximation and Round off Error, Truncation Errors. Intermediate Value Theorem.  

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. 

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.  

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. 

Numerical Differentiation: High Accuracy, Differentiation Formula, Forward and Backward and Center Difference Formula, MATLAB Program of Numerical Differentiation. 

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 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 using modern tools like MATLAB.  

References: 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Gerald/Wheatley, Applied Numerical Analysis, Sixth editio 

Journals, Web Materials, YouTube Videos etc. 

2 

Chapra, Numerical Methods for Engineers, Sixth edition 

  

Course Code: CSE 2205-0613 

Course Title: Competitive Programming-II 

Course Type: Lab          

prerequisite: CSE 2105-0613 

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 getting themselves certified for the IT industry. The outline focuses on efficient implementation of Data Structures and algorithms using STL. Also, different problem solving paradigms as well as set up competitive mindsets among the individuals.  

Course Content 

Introduction to Competitive Programming: Problem solving platforms, Tools and libraries, Contest ranking, Career path, Interview overview 

Introduction to C++: Syntax, Library functions, Input, Output 

Warm-up contest 

Problem solving paradigm: Implementation, Greedy, Brute force, Data structure and algorithm, string, constructive algorithm, graph, Dynamic programming 

STL: Standard template libraries, use in previous codes to optimize 

String in C++: library functions, string with STL  

Array in C++: array with STL 

Advanced contest-I 

Dynamic array: Vector, list, pointer, iterator 

Set, multiset 

Stack, Queue  

Map: Ordered map, unordered_map 

Advanced contest-II 

Number theory: Prime number and time complexity optimization, sieve of Eratosthenes, Prime factorization, GCD, LCM 

Advanced contest-III 

Recursion 

Graph Theory: BFS, DFS, problem solving, 2D grid 

Tree: Construct tree, tree manipulation, node finding  

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 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Object Oriented Programming With C++, Balagurusamy  

Problem solving platforms, webinars, Web Materials,  etc. 

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 

  

Course Code: CSE 3151-0714 

Course Title: Digital Logic Design 

Course Type: Theory         

 prerequisite: EEE 1211-0714 

 Credits: 3               

Contact Hours: 42            

Total Marks: 100 

 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:  

Number systems: Representation of numbers in different bases, Addition and subtraction in different bases, Complement: Subtraction using complements, Binary multiplication & division. 

Binary codes: Different coding system, Boolean algebra, various gates, Sum of products and product of sums, Standard and canonical forms and other logical operations. 

Simplification of Boolean functions: Karnaugh map method, Tabular method of simplification; Implementation of logic circuit using various gates, Universal gates. 

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. 

Flip-flops: SR, JK, Master slave, T and D type flip-flops and their characteristic tables & equations; Triggering of flip-flops, Flipflop, Excitation table. 

Sequential circuits: Introduction to sequential circuits, Analysis and synthesis of synchronous and asynchronous sequential circuits. 

Counters: Classifications, Synchronous and asynchronous counter design and analysis, Ring counter, Johnson counters, Ripple counter and counter with parallel load. 

Registers: Classification, Shift registers, Circular registers and their applications and registers with parallel load. Basic Concept of Application Specific IC (ASIC) design. 

Digital IC logic families:  

Brief description of TTL, DTL, RTL, ECL, I2L, MOS and CMOS logic and their characteristics, principles of operation and application. 

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 the 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 the digital electronic and logic circuits using digital integrated circuits. 

References: 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Digital Logic and Computer Design (4th Edition) - M. Morris Mano (2007) 

Journals, Web Materials, etc. 

2 

Digital Computer Electronics (3rd Edition) - Albert P. Malvino, Jerald A Brown (2001) 

 

3 

Modern Digital Electronics by R.P. Jain 

  

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 a 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 Multiplexer and Demultiplexers. 

Design and Circuit construction of Combinational Circuit using 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 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 the problems efficiently on a model of computation, computational process, their limits and the elementary ways in which a computer works. 

Course Content 

Overview: Introduction to TOC, Different Layers of TOC, Finite State Machine, Context Free Grammar, Turing Machine, Undecidable 

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 

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 

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 

Turing Machine: Introduction to Turing Machine, Turing Machine Problem Solving, Turing Machine Programming Techniques, Non-Deterministic Turing Machine, Decidability, Universal Turing Machine 

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, grammars, 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Michael Sipser, Introduction to Theory of Computation, Published by Thomson, 2nd Edition.   

Journals, Web Materials,  etc. 

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) 

  

HRM 1103 - 0413: Principles of Management 

Course Type: Theory          

Prerequisite: None 

Credits: 3          

Contact Hours: 42        

Total Marks: 100 

Year/Level: 1st                       

Semester/Term: 1st 

  

Rationale of the Course 

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, role of managers. 

  

  1. Management and environment:internal environment, external environment, how management aligns to those environmental aspects in terms of sustainable development. 

  

  1. Planning:Define planning, planning process, types of plans, levels of planning, aligning planning with strategy. 

  

  1. Organizing:Define organizing, explain organizational chart and structure, organizational design, types of organizations, define staffing, define work groups and teams.

  

  1. Motivation: Define motivation, motivational theories. 

  

  1. Leading:Define leading, leadership theories. 

  

  1. Controlling:Define controlling, types of controlling, controlling process. 

  

  

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 setting. 

  

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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Fundamentals of Management (2016) by Ricky W. Griffin. 

Journals, Web Materials, YouTube Videos etc. 

2 

Management (2006) by Robert Kreitner. 

 

3 

Management (1988) by  Heinz Weihrich and Harold Koontz 

  

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 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 a critical scrutiny of their own ethics by those from other professions.  

The general principles of 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, the responsibility of engineers to the environment and society. 

Course Content 

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. Obligation of an engineer to the clients. Attitude of an engineer to other engineers. Measures 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 of 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, scope of ethics and different branches of ethics, social change and emergence of ethics, history and 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 human qualities of the engineers. 

CLO5: Would be able to implement the 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 syllabus so that the students can be skilled at the accounting equation, Conceptual framework of accounting, completing the process of 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 

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, Ethics in Accounting. 

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. 

Preparation of Worksheet: Basis of Accounting, Recording of Adjusting Entries. Correcting Entries, Closing Entries, Post Closing Trial balance, Reversing Entries, Worksheet for Preparing Financial Statements. 

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. 

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 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 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Accounting Principles by Kieso, D. E & Weygantt, E. I. 

Journals, Web Materials,  etc.. 

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. 

 

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, 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 

Introduction to Computer Networks: IP address, VLSM, application, transport, and data link layer protocols, Vlan-VTP, IPv6, and NAT.  

Fundamentals of signals and data communication: Network Topology, Digital modulation: ASK, FSK, Multiple access techniques: TDM, FDM.  

Protocol hierarchies: Demonstration of the OSI model's fundamental concepts and description of the characteristics of various layers. 

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.) 

 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.) 

Introduction to transport layer: UDP, TCP; Principles of Reliable data transfer, Principles of congestion control, TCP, Congestion control; 

Introduction to Network and Data Link Layer:  Network layer protocols and routingMultiple 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 

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 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 

 

 

Serial no. 

Textbooks 

Others Learning Materials 

1 

Forouzan, B. A., Coombs, C. A., & Fegan, S. C. (2001). Data communications and networking. Boston: McGraw-Hill. 

Journals and  Web Materials, etc. 

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. 

 

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, Setup 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 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 elicitation of requirements from top level stakeholders and making necessary documentation. Moreover, culminating 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 specification document  

Able to develop tentative methodology  
Course Learning Outcomes (CLOs) 

CLO1: Able to develop systems’ requirement specification 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 identify its standards. 

References 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Project Management, 4th edition, stephen hartley  

Problem solving platforms, webinars, Web Materials 

2 

Software Requirements & Specifications, by Michael J. Jackson and Michael Jackson 

  

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 

  

  

Rationale of the Course 

  

This course intended to enable the students to understand and apply the fundamental techniques and practical features of construction of compiler and translation process that underlie the practice of various phases of compiler construction. 

Course Content 

  

Introduction to Compiler: Interpreter and Compiler, Typical Implementations, Hybrid Approaches, Brief introduction of the phases of the compiler, Why study compilers. 

Lexical Analysis: Token, Lexical Error, Manage Input Buffer, Kleene Closure, Regular Expression, Regular Language, Finite State Automata, Thomson’s Construction, Hopcroft’s Algorithm, Partitioning. 

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 

Intermediate Code Generator: Three address code, Quadruples, Triples, Indirect Triples, Translating Expressions, Synthesized code and place attributes. 

 Code Optimization: Basic blocks and control flow graphs, Transformation on basic block, Structure preserving transformation, Algebraic Transformation, Loops, Loop Optimization, Array Indexing, Common subexpression elimination 

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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Compilers: Principles, Techniques & Tools (2nd ed)- Alfred V Aho, Monica SLam, Ravi Sethi, and Jeffrey D Ullman, Pearson/Addison Wesley (2006). 

Journals, Web Materials, etc. 

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 

 

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, tokenizers and to be able to write the code using Python Programming language to understand the construction of 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 lexical analyzer for validating operators 

Write a program to simulate 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 abstract syntax tree generated by the parser. The instruction set specified in Note 2 may be considered as the target code. 

Course Learning Outcomes (CLOs) 

CLO1: Able to identify and implement the working principles of computer systems and its 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 practice 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 Content: 

Introduction to Basic Database Concepts: The Course Outline and Objective, Database Definition, Importance of Databases, Shortcomings of Traditional File Processing System, Levels of Data, Different Types of Database Users, History of DBMSs, Advantages and Disadvantages of DBMSs. 

Database Architecture: Three Level Schema Architecture, Data Independence, Database Languages Database, Data Model and DBMS, Functions and Components of a DBMS Multi-user DBMS Architectures. 

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. 

Fact-Finding Techniques: What facts are collected, Techniques, A worked example 

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. 

Entity-Relationship Modeling Case Studies 

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. 

Normalization: Objectives, Functional Dependency, Inference Rules, First Normal Form, Full Functional Dependency, Second Normal Form, Transitive Dependency, Third Normal Form, Boyce-Codd Normal Form. 

Data Manipulation Languages: Relational Algebra: Unary and Binary operations, Selection, Projection, Cartesian Product Different types of Joins, Union, Intersection, Division. 

Relational Algebra Practice 

SQL Queries: Insert, Delete, Select, Update, Where, Order by 

SQL Queries with Joins: Types of joins, Sub queries 

Indexing: Types of SQL indexing 

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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Database System Concepts, Abraham Silberschartz, Henry F. Korth and S Sudershan, Published by McGraw-Hill, 7th Edition. 

Journals, Web Materials,  etc. 

2 

Database Systems: Design, Implementation, and Management, by Carlos Coronel & Steven Morris & Peter Rob 

 

3 

Beginning Oracle SQL for Oracle Database 12c, 3rd edition,  

  

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 implementation of database schemas and user interfaces. 

  

Lab Tasks 

  

Draw E-R diagram and convert entities and relationships to 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, 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 relation 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. 

References Books: 

  

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Database System Concepts, Abraham Silberschartz, Henry F. Korth and S Sudershan, Published by McGraw-Hill, 7th Edition. 

Journals, Web Materials,  etc. 

2 

Database Systems: Design, Implementation, and Management, by Carlos Coronel & Steven Morris & Peter Rob 

 

3 

Beginning Oracle SQL for Oracle Database 12c, 3rd edition,  

 

  

  

  

  

  

  

  

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 implementation of database schemas and user interfaces. 

  

Lab Tasks 

  

Draw E-R diagram and convert entities and relationships to 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, 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 relation 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. 

References 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Md. Rafiquzzaman, Microprocessor and Microcomputer Based System Design, Published by CRC Press, 2nd Edition. 

Journals, Web Materials,  etc. 

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.  

  

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 microprocessor and assembly language. 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, OUTDEC 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

PC Ytha Yu and Charles Marut, Assembly language Programming and Programming Organization of the IBM 

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 & its 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 website with 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 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 on data definition language and data manipulation language 
     Experiment on database connection and session and cookies in PHP/JSP/ASP.NET 
     Study of JavaScript and applying JavaScript into web pages 
     Create a web page with HTML, CSS, JavaScript & PHP/JSP/ASP.NET 
     Study with framework: LARAVEL/JSP/JSOUP/.NET 
     Working for the team project with bitbucket and prepare demo 
     Working for 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, form validation mechanisms, use the JavaScript frameworks jQuery and AngularJS and ensure client-side web security. 

References 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Jon Duckett “Beginning Web Programming” WROX 

Journals, Web Materials, YouTube Videos etc. 

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 

  

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 design and development of computerized systems considering ethical, technical and financial issues. Based on the market analysis and documentations, design the system’s architecture and finally integrate hardware and software for making a complete viable product. 

Course Outlines: 

Able to complete detailed design & modeling 

Prepare initial UI design and hardware connection  

Complete whole implementation of software and hardware and integrate 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 chnges. 
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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Project Management, 4th edition, stephen hartley  

Problem solving platforms, webinars, Web Materials 

2 

Software Requirements & Specifications, by Michael J. Jackson and Michael Jackson 

  

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 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 Content 

  

Software Engineering: Software Engineering Principles, Software Processes, SDLC, SDLC Models, Requirement Engineering 

Models: Waterfall Model, RAD Model, Spiral Model, V-model, Incremental Model, Agile Model, Iterative Model, Big-Bang Model, Prototype Model 

Software Management: Project Management, Activities, Project Management Tools 

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 

Project Planning: Software Project Planning, Software Cost Estimation, COCOMO Model 

Risk Management: Risk Management Activities, Project Scheduling, Personnel Planning 

Software Requirement: Software Requirement Specifications, Requirements Analysis, Data Flow Diagrams, Data Dictionaries, Entity-Relationship Diagram 

S/W Configuration: Software Configuration Management, SCM Process, Software Quality Assurance, Project Monitoring & Control 

Software Quality: ISO 9000 Certification, SEICMM, PCMM, Six Sigma 

Software Design: Software Design Principles, Coupling and Cohesion, Function Oriented Design, Object Oriented Design, User Interface Design 

Software Reliability: Software Failure Mechanisms, Software Reliability Measurement Techniques, Software Reliability Metrics, Software Fault Tolerance 

Software Reliability Models: Jelinski & Moranda Model, Basic Execution Time Model, Goel-Okumoto (GO) Model, Musa-Okumoto Logarithmic Model 

Software Maintenance: Causes of Software Maintenance Problems, Software Maintenance Cost Factors 

  

  

Course Learning Outcomes (CLOs) 

  

CLO1: Able to explain a process model for a software project development. 

  

CLO2: Would be able to analyze and prepare SRS (Software Requirement Specification), design document, 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Software Engineering A Practitioner's Approach by Roger S. Pressman, 7th edition, McGraw Hill, 2010. 

Journals, Web Materials,  etc. 

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 

  

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 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 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, integration testing for a sample code of the suggested system.  

Perform Estimation of effort using FP Estimation for chosen system.  

To Prepare timeline chart/Gantt Chart/PERT Chart for 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 for people management, process management, project plan 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 gaining knowledge about society's demand. 

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 a good knowledge on cybersecurity and law to avoid any kind of unethical and illegal issues for the benefit of thyself and the society. 

 Course Contents:  

Introduction to Cybersecurity: Security principle: CIA Triad, Infamous Cybercrimes, Cybercrime Taxonomy, Civil vs Criminal Offenses. 

Basic Elements of Criminal Law: Branches of Law, Tort Law, Cyberlaw enforcement, Cyberlaw Jurisdiction. 

Overview of US Cybersecurity Law: History of Resolving Cybersecurity Disputes, Alternate Dispute Resolution, Data Breach Lawsuits. 

Legal Doctrine: Duty of Care Doctrine, Failure to Act Doctrine, Reasonable Person Doctrine. 

Procedural Law: Rules of Criminal Procedure, Computer Crime Laws, False Claim Act. 

Data Privacy Law: Common Law of Privacy, Privacy Laws, Data Breach Laws, Data Breach Litigations. 

Personal Security: Personal Liability, Directors and Officer’s Insurance’, Preemptive Liability, Whistleblower Protections. 

Data Encryption Law: Overview of Cryptology, Cryptology Law, International Cryptography Laws. 

Standards and Regulations: International Statutes, Domestic Statutes, Industry Statutes. 

Cybersecurity Law Program: Model and Architecture, Staffing and Roles, Policies and Procedures, Technology. 

Cyber Liability Insurance: Coverage Categories, Policy Restrictions, Claim Processes. 

Compliance Auditing: Critical Audit Matters, Internal vs External Auditing, Auditing Standards. 

Developments in Cybersecurity Law: Future of Cyber Law, Impact of Technology on Cybersecurity Law. 

International Cyber and Privacy Law:  Harmonization of International Cyberlaws, 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Jeff Kosseff, Cybersecurity and Law,  Publisher: Wiley 

Journals, Web Materials, YouTube Videos etc. 

2 

Schreider Tari, Cybersecurity Law, Standards and Regulations: 2nd Edition 

  

 

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 designing and building increasingly more sophisticated and meaningful mobile applications to understand the philosophy to improvise Android development building blocks and incorporation with each other.   

 Lab Task 

Rewinding of Object Oriented Programming Concept in JAVA. 

Problem Assessment of OOP Inheritance with some example. 

Problem Assessment of OOP Exception Handling and Multiple Threading Concept 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 android SDK 

Create, compile and manifest the first “Hello World” Android app project. 

Introduction of Explicit and Implicit intents and solution to intent challenges. 

Create application of event handlers with onClick and onKeyDown.  

Introduction and Solution of Fragment, RecyclerView and CardView 

Create application with android user interface functions 

Create 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 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 Content 

  

Overview: Introduction, Software Execution, History and Hardware, OS Structures 

Process Management: Processes, Scheduling, Inter process communication, Synchronization  

Deadlock: Resource allocation and deadlock, deadlock detection, prevention and recovery 

Memory Management: Memory allocation, Paging and segmentation, Virtual memory 

File System Management: File system interface, File system implementation 

IO Management: IO systems, Disk management 

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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Operating System Concepts, A. Silberschart, Peter B. Galvin and Greg Gagne, Published by Willey, 10th Edition.   

Journals, Web Materials,  etc. 

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 

 

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 problem 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 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 perspective. 

  

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 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 perspective. 

  

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 

  

Introduction to Data Mining and Machine Learning: Applications of data mining, data mining tasks, motivation and challenges, types of data attributes and measurements, 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, feature selection methods.  

Data Pre-processing: Supervised and Unsupervised data, aggregation, sampling, dimensionality reduction, Feature Subset Selection, Feature Creation, Discretization and Binarization, Variable Transformation. 

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.  

Model Evaluation: Holdout Method, Random Sub Sampling, Cross-Validation, evaluation metrics, confusion matrix. 

Association Rule: Transaction data-set, Frequent Itemset, Support measure, Apriori Principle, Apriori Algorithm, Computational Complexity, Rule Generation, Confidence of association rule.  

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, DBSCAN: The DBSCAN Algorithm, Strengths and Weaknesses. 

Regression: Linear regression with one variable, linear regression with multiple variables, gradient descent, logistic regression, over-fitting, 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 preproces, cleaning and transformation of data.. 

CLO2: Able to train the classifier and evaluate its performance, use 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 itemsets and association rules on a regular basis. 

CLO5: Able to solve complex problems based on regression algorithms. 

References 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Han, J., Kamber, M.,& Jian,P. (2011). Data Mining: Concepts and Techniques. 3rd edition. Morgan Kaufmann 

Journals, Web Materials,  etc. 

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. 

 

6 

Hand, D., & Mannila, H. & Smyth, P. (2006). Principles of Data Mining. Prentice-Hall of India 

 

7 

Pujari, A. (2008). Data Mining Techniques. 2nd edition. University Press. 

  

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 revolution with impacts and implications for 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 

  

Introduction to Artificial Intelligence: What is Artificial Intelligence, Knowledge based systems, Problem solving by searching, Early Works of AI, Classic AI problems, Inference Engine 

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 

Advanced Searching: Uninformed or Blind Search, Informed or Heuristic Search, Game Playing with Adversarial Search, Local Search 

Knowledge Representation and Reasoning under Uncertainty: Declarative vs Procedural Search, Fundamental Concepts of Logical Representation, Propositional Logic, First Order Logic, Planning 

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 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, reasoning, and demonstrate practical experience by experimenting real-world problems with the learnt algorithms. 

References 

  

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Stuart J. Russell and Peter Norvig, Artificial Intelligence: Modern Approach (new edition), USA, Prentice Hall, 2006 

Journals, Web Materials, YouTube Videos etc. 

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. 

  

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 the knowledge based problem solving with relevant basic programs and their underlying theoretical concepts. 

Lab Task 

Introduction with 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 problem 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 its 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 in time. Main aspects of software project management are high-level project overview, task management, reporting and time tracking. The project management is to bring about beneficial change or added value 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, proposal preparation. 

Designing and Implementation: Build prototype of the project, architecture, analyzing pros and cons, implementation using suitable framework, platforms, communication, security 

Management: A large engineering software system management, client management, managing software project teams, project planning and scheduling, risk management, 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 team work, participating in each stage of the project, project testing, troubleshooting and assembling the overall project. 

 References: 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Murali K. Chemuturi and Thomas M. Cagley Jr., Mastering Software Project Management: Best Practices, Tools and Techniques, published by J. Ross Publishing. 

Web Materials,  etc. 

2 

Andrew Stellman and Jennifer Greene, Applied Software Project Management, published by O’Reilly Media.  

  

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 on 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:  

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 Data Scientists Do? 

 Data Preparation: Concepts of Data and Big Data, Variables, Dataset, Database, Extraction, Transformation and Loading (ETL) 

Exploration: Univariate and Bivariate 

Modeling: Classification, Regression, Clustering and Association Rules 

Python Libraries: NumPy, pandas, matplotlib, SciPy, scikit-learn, statsmodels. 

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, String Manipulation. 

Data Wrangling: Hierarchical Indexing, Combining and Merging Data Sets Reshaping and Pivoting. 

Data Visualization: Basics of matplotlib, plotting with pandas and seaborn, other python visualization tools. 

Data Aggregation and Group operations: Group by Mechanics, Data aggregation, General split-apply-combine, Pivot tables and cross tabulation. 

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, Moving Window Functions. 

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 Practica 

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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

McKinney, W.(2017). Python for Data Analysis: Data Wrangling with Pandas, NumPy and IPython. 2nd edition. O’Reilly Media. 

Journals, Web Materials,  etc. 

  

http://www.saedsayad.com/data_mining_map.htm 

2 

O’Neil, C., & Schutt, R. (2013). Doing Data Science: Straight Talk from the Frontline O’Reilly Media 

 

Course Code: CSE 4164-0613 

Course Title: Basic Graph Theory 

Course Type: Theory           

Pre- requisite:  

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: 

 Fundamentals of Graph theory: Graphs and their applications, Basic graph terminologies, Basic operations on graphs, Graph representations, Degree sequence and graphic sequence. 

Theory of Trees: Paths, cycles, and connectivity; Trees and counting of trees; Distance in graphs and trees. 

Algorithms: The Euler formula, Hamilton routes, planar graphs, Ear decomposition; Graph coloring; 

Graph Problems: Graph labeling: Matching and covering, trees in sorting and prefix codes;  

Methods: Network methods have the shortest path methodology, the minimal spanning tree technique, 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 

 

 

SL No. 

Textbooks 

Others Learning Materials 

1 

NarsinghDeo, Graph Theory with Applications to Engineering and Computer Science, Published by Prentice-Hall of India Pvt Ltd. 

  

Journals, Web Materials,   etc. 

2 

Douglas B. West, Introduction to Graph Theory, Published by Pearson, 2nd Edition.  

  

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 student’s understanding about 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 

Introduction: Wireless Networking History, Wireless Certifications, Standard Organizations, WiFi Alliance, 802.11 Standards 

Wireless Basics: How Wireless Works, Wireless SWOTs, Wireless Signal Characteristics, Wireless Topologies 

Understanding RF: RF Behaviors, RF Math, Rule of 10s and 3s, Understanding Beamwidth 

Wireless Signaling: Bands Channels and Frequencies, What is Spread Spectrum, Common Wireless bands, 2.4 GHz Basics, 5 GHz Basics, Bandwidth and Throughput 

Signal Transmission: Antenna Basics, Radiation Patterns, Parabolic and Grid Antennas, MIMO, Understanding of Attenuators 

Wireless LANs: Wireless LAN Basics, Access Point Basics, SSID Basics, BSS and BSSID, Access Point Modes, CSMA/CD and CSMA/CA 

Wireless Security Fundamentals: Wireless Security Challenges, Wireless Security Policy, AAA, Data Protection, WEP, WPA and WPA2, MAC Filtering 

WLAN Design: Site Survey, Customer Education, Security Requirements, AP Placement and Settings, Coverage Analysis 

 Course Learning Outcomes (CLOs) 

  

 CLO1: Learn the basic technological concept Wireless Network 

 CLO2: Competent to understand the design and operation methodologies of Wireless Network. 

 CLO3: Able to design a wireless network. 

 CLO4: Able to gain a solid understanding about how Wireless Network is solving variant complex engineering problems related to communication technologies. 

 References 

  

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Matthew Gaust, 802.11 Wireless Networks: The Definitive Guide 

Journals, Web Materials,   etc. 

2 

Adeel Javed, Building Arduino Projects for the Internet of Things: Experiments with Real World Applications, Published by Apress 

  

 

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, definition and characteristics, the problem it’s solving, Service Models, Service providers and a lot more from this course. 

Course Contents:  

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 

  

Attributes of Cloud Computing: Multi-tenancy, Massive Scalability, Elasticity 

Infrastructure-as-a-Service(IaaS): Introduction to IaaS, Resource, Virtualization, Case Studies 

  

Platform-as-a-Service(PaaS): Introduction to PaaS, Cloud Platform, Management of Computation and Storage, Case Studies. 

  

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, interoperability. 

  

CLO4: Competent to research and attempt to generate new ideas and innovations in cloud computing. 

  

References: 

  

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Barrie Sosinsky.Cloud Computing Bible. Wiley, 1st edition, 2011 

Journals, Web Materials, YouTube Videos etc. 

2 

John Rhoton.Cloud Computing Explained: Implementation Handbook for Enterprises, Recursive Press, 1st edition 2009. 

  

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: 

Introduction to Bioinformatics: Introduction to biology, biological databases, and high-throughput data sources; Overview of bioinformatics problems 

Sequence Analysis and Alignment: Statistical significance of alignments; Suffix Trees; Suffix Arrays; Patterns, Profiles, and Multiple Alignments; Hidden Markov Models; Multiple Sequence Alignment Algorithms 

Introduction to Protein StructuresProtein Structure Prediction; Structural Alignment of Proteins; Microarray data normalization, analysis of Clustering techniques 

Introduction to Systems Biology: Gene regulatory networks 

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 about 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 the overview about biological macromolecular structures and structure prediction methods. 

References: 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

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. 

 

 

 

 

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: 

Introduction: Historical evolution of robotics, Importance of material goods production in modern society, Robots role in modern production, State of the art in the industrial robotics, IFR statistics 

Mechanics of Robotics: Robot characteristics, subsystems and classification, Robot mechanical system: links, bearings, shafts, gearboxes, grippers 

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. 

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 

Robot Dynamics: Forward and Inverse Dynamic, Euler-Lagrange formulation, joint and Cartesian forces,  Equations of motion using Euler-Lagrange formulation, Newton Euler formulation  

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. 

Robot Actuation Systems: Actuators: Electric, Hydraulic and Pneumatic; Transmission: Gears, Timing Belts and Bearings, Parameters for selection of actuators. 

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 

Control Hardware and Interfacing: Embedded systems : Microcontroller Architecture and integration with sensors, actuators, components, Programming Applications for Industrial robot - programming in – VAL II 

Robot Programming: Motion oriented and task oriented languages, Robot application in typical operations and tasks, Mobile robots kinematics, path planning and control, Research and future of robotics.  

AI in Robotics: Applications in unmanned systems, defense, medical, industries, etc. 

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, the 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 the analytical, planning, presentation and teamwork skills. 

CLO5:  Able to develop and deepen the programming concepts related to robotics. 

References: 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Bruno Siciliano and OussamaKhatib, Springer Handbook of Robotics, Published by Springer, 2008. 

Journals, Web Materials,  etc. 

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 

 

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:  

Introduction: Introduction to  Entrepreneurship, Management and Its Evolution, Roles of an Entrepreneur. 

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. 

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 . 

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.  

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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Rachid Benlamri & Michael Sparer, Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy: Proceedings, Publisher: Springer 

Journals, Web Materials,  etc. 

2 

Morrill, Richard L. , Strategic Leadership 

  

 

Course Code: CSE 4277-0612 

Course Title: Network and Server Administration 

Course Type: Theory              

Pe- 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: 

Aspects of computer communications from a theoretical standpoint: Networking overview, IP addressing basics.  

The function of the Computer network: network planning, DHCP, DNS, FTP, HTTP, etc. 

The architecture of computer networks: implementing and managing WINS,  securing network traffic, remote access, Internet authentication service.  

Software used in computer networks to manage systems: routing, naming, configuring file services, configuring and monitoring print services,  maintaining and updating Windows, 

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 

 

 

SL No. 

Textbooks 

Others Learning Materials 

1 

Thomas Limoncelli, Christina Hogan and Strata Chalup, The Practice of System and Network Administration, published by Addison-Wesley Professional. 

  

Journals, Web Materials, etc. 

2 

AnandaDeveriva, Network Administrators Survival Guide, published by Cisco Press. 

  

  

Course Code: CSE 4278-0612 

Course Title: Network and Server Administration Lab 

Course Type: Lab             

Pe- 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 set up Web servers and terminal services 
 
CLO2: competent to configure physical devices, as well as implement, administer, and monitor 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 Content: 

Introduction: Application areas of Computer Graphics, overview of graphics systems, Video-display devices, Raster - scan systems, Random scan systems, Liquid Crystal Display (LCD), graphics monitors and workstations and input devices. 

 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.  

Filled area primitives: Clipping and Viewport, Flood Fill Algorithm, Boundary Fill Algorithm, Scan-Line Polygon Fill Algorithm.  

 2D Transformations: Introduction of Transformation, Translation, Scaling, Rotation, Reflection, Shearing, Matrix Representation, Homogeneous Coordinates, Composite Transformation, Pivot Point Rotation. 

 2D-Viewing: The Viewing Pipeline, Viewing Coordinate Reference Frame, Window to Viewport Coordinate Transformation, 2-D Viewing Functions. 

 Clipping Techniques: Clipping, Point Clipping, Line Clipping, Midpoint Subdivision Algorithm, Text Clipping, Polygon, Sutherland-Hodgeman Polygon Clipping, Weiler-Atherton Polygon Clipping. 

3-D Geometric transformations: Translation, rotation, scaling, reflection and shear transformations, composite transformations.  

3-D viewing: Viewing pipeline, viewing coordinates, view volume and general projection transforms and clipping.  

Computer animation: Design of animation sequence, general computer animation functions, raster animation, computer animation languages, key frame systems, motion specifications. 

  

Course Learning Outcomes (CLOs) 

CLO1: Able to explain the applications, areas, and 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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Fundamentals of Computer Graphics, Peter Shirley and Steve Marschner, Third Edition.(A.K.Peters Publication house) 

Journals, Web Materials,  etc. 

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. 

  

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 slope.  

Write a program to draw a line using the DDA algorithm.  

Write a program to draw a line using Mid-Point algorithm.  

Write a Program 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 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 a tetrahedron to form 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 Bezier Curve algorithm.  

Develop a menu driven program to fill the polygon using 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 signal transmission through different media. Different wireless techniques, satellite, cellular telephony, different types of modulation and demodulation, and performance of data transmission with congestion and quality control are discussed here.  

 Course Outlines: 

Introduction to wireless networks 

Data and signal: Transmission impairment, attenuation, distortion, noise,  

Wireless transmission 

Frequencies 

Modulation 

Demodulation 

Different types of wireless communication networks 

Wireless WAN: Frequency-Reuse Principle, Transmitting, Receiving, Roaming, First Generation, Second Generation, Third Generation 

Cellular Telephone: GSM, IS-95, GSM architecture  

Satellite Network: Orbits Footprint, Three Categories of Satellites, GEO Satellites, MEO Satellites, LEO Satellites 

Data rate limit: Noiseless Channel: Nyquist Bit Rate  Noisy Channel: Shannon Capacity  Using Both Limits  

Performance: Bandwidth, Throughput, Latency (Delay), Delay Product  

Congestion control: Data traffic, Traffic descriptor, Loop congestion, Flow characteristics, flow classes 

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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Cory Beard and William Stallings, Wireless Communication Networks and Systems (ISBN: 0133594173, available online). 

Problem solving platforms, webinars, Web Materials, etc. 

2 

David Tse and Pramod Viswanath, Fundamentals of Wireless Communication [T & V] (available online). 

  

 

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 type of problem solving 
CLO2: Able to generate different transmission graph and waveforms using Matlab 
CLO3: Able to develop and implement different modulation and demodulation techniques, ASK, FSK, PSK. 

References 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Cory Beard and William Stallings, Wireless Communication Networks and Systems (ISBN: 0133594173, available online). 

  

Problem solving platforms, webinars, Web Materials,  etc. 

2 

David Tse and Pramod Viswanath, Fundamentals of Wireless Communication [T & V] (available online). 

  

 

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 specification 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 

Introduction to Software Architecture: introduction to software, Organogram, SDLC Concept, Software Types, Information Gathering Process. 

Feasibility Study: Economical, Technical and Behavioral Study, SWOT Analysis, Cost-Benefit Analysis 

Diagrams: UML Design, Context Diagram, Activity Diagram, Data Flow Diagram, Use Case Diagram, Mockup Design 

Deployment: Deployment Diagram, Three Golden Rules 

SRS: SRS Introduction, Functional and Non-functional Requirements, SRS Design  

  

Course Learning Outcomes (CLOs) 

CLO1: Students will learn the basic concept System Architecture 

CLO2: Competent to design a System Architecture. 

CLO3: Able to analyze different types of system designs and test the feasibility. 

CLO4: Competent to solve real project related problems related to System Architecture and Design. 

References: 

Learning Materials 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

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

Journals, Web Materials, YouTube Vides etc. 

2 

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

  

  

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 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 softwares. 

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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

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

Journals, Web Materials, YouTube Videos etc. 

2 

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

  

  

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 

Introduction: What is DDBMS? Distributed data processing; Problem regions; DDBS advantages and downsides A brief introduction to database and computer network principles. 

Architectures: Transparencies in a distributed database management system; architecture of a distributed database management system; global directory concerns. 

Design: Fragmentation, Data allocation, Alternative design methodologies, Distributed design concerns. 

Data control: Semantic Integrity Control; View management; Data security 

Query Processing: Query processing objectives, query processor characteristics, query processing layers, query decomposition Data distribution localization. 

Query Optimization: Factors that influence query optimization; centralized query optimization; fragment query ordering; Algorithms for query optimization that are distributed. 

Transaction management: The transaction idea; Transaction Management Goals; Transaction Characteristics; Transaction Taxonomy. 

Concurrency control: Deadlock management; Concurrency control in centralized database systems; Concurrency control in DDBSs; Distributed concurrency control techniques; 

 Reliability: Issues with DDBS reliability; Failure types; Reliability approaches; Commit processes; Recovery protocols 

Parallel database systems: Load balancing; parallel architectures; parallel query processing and optimization 

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 

 

 

SL No. 

Text Books 

Others Learning Materials 

1 

Distributed Systems: Principles and Paradigms by Andrew S. Tanenbaum and Maarten Van Steen 

Journals, Web Materials, YouTube Vides etc. 

  

https://cs.uwaterloo.ca/~tozsu/courses/cs748t/c748t.htm 

  

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 to design and develop complex projects using distributed database functions and query based on advanced models - distributed databases to solve real-life problems. 

 Lab Contents 

Introduction distributed database management system 

Analysis and Design a sample distributed database system 

Distributed database design for any store management system  

Implement Deadlock Detection Algorithm for distributed database using waitfor 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 (F

amily Relations) 

Study and Working of WEKA Tool 

Query Processing – Implementation of an Efficient Query Optimizer 

Designing XML Schema for Company Database 

Course Learning Outcomes (CLOs) 

CLO1: Students able to understand the steps of query processing, optimization techniques are applied to Distributed Database. 

CLO2: Able to understand Transaction management and compare various approaches to concurrency control in Distributed Database. 

CLO3: Able to apply various algorithms and techniques for deadlock and recovery in Distributed Database. 

Duration of Terms 

The duration of each of Term-I and Term-II will be as follows:  

Term - I 

 

 

  

Weeks 

  

Classes 

14 

  

Recess before Term Final Examination 

02 

  

Term final examination 

03 

  

55Total 

19 

  

Inter Term Break 

02 

  

  

Term - II 

 

 

 

 

 

Classes 

14 

  

Recess Before Term Final Examination 

02 

  

Term Final Examination 

03 

  

Total 

19 

  

Holidays, Vacations and Result Publication 

02 

  

Grand Total 

52 

  

Theoretical Courses 

 One Lecture per week per term will be equivalent to 1 (one) credit. There shall be at least 14 contact hours for each theoretical credit point in each Term. 

 There shall be normally 3 (two) contact hours in a week and 60 contact hours in a Term for each credit of Practical/Sessional course. 

Project and Thesis 

The students will be allowed nine working hours per week exclusively dedicated to Project Work. Credit for Project and Thesis will be 3.00. 

Definition of Courses 

 Syllabus shall consist of several courses. Following structure shall be followed to articulate the courses. There shall be 05 (Five) types of courses as follows: 

Theoretical Courses: Includes Class-teaching, Open discussion, Academic tasks etc. 

Practical/Sessional Courses: Includes Laboratory experiment/Field Work etc. 

Project and Thesis: During the Level-IV of study each student will be required to complete a Project and Thesis in the relevant field of their specialization. For such work the students will be guided by a teacher of the concerned Department. 

Comprehensive Viva: The Comprehensive Viva will cover the whole 4-years course of study. No specific class hour will be assigned for the Comprehensive Viva. 
Grading/ Evaluation 

For evaluation purposes all credit courses will be equivalent to 100 Marks. 

Grades and Grade Scale: 
Grades and Grade Point will be awarded on the basis of marks obtained in the Written, Oral or Practical Examinations/Laboratory performances according to the following scheme: 

Marks obtained (%) 

Grade 

Grade point 

80 to 100 

A+ 

4.00 

75 to 79 

A 

3.75 

70  to 74 

A- 

3.50 

65 to 69 

B+ 

3.25 

60 to 64 

B 

3.00 

55  to 59 

B- 

2.75 

50 to 54 

C+ 

2.50 

45 to 49 

C 

2.25 

40 to 44 

D 

2.00 

Less than 40 

F 

0.00 

  

I 

Incomplete 

Distribution Marks  

Theory 

  

  1. Continuous Assessment 

  

                (i) Class Attendance 

: 15% 

                (ii) Class Test/Quiz 

: 15% 

                (iii) Assignment/Presentation 

: 20% 

  1. Mid Term Exam 

: 20% 

(c) Term Final Exam 

: 30% 

Total 

100% 

Practical/Sessional/Lab 

  

  1. Continuous Assessment 

  

             (i) Class Attendance 

: 10% 

             (ii) Performance 

: 30% 

Total 

40% 

  1. Final Exam 

  

               (i) Experiment 

: 20% 

               (ii) Report 

: 20% 

               (iii) Viva-Voce 

: 20% 

Total 

60% 

  

  

Project or Thesis 

  

  1. Continuous Assessment 

: 40% 

  1. Final Exam 

: 60% 

Total 

100% 

Comprehensive Viva 

All subject’s 100% 

  1. The overall or Cumulative GPA gives the cumulative performance of the student from Term-I up to any other Term to which it refers and is computed by dividing the total grade points accumulated up to the date by the total credit hours. 
  1. Both GPA and CGPA will be rounded off to the second place of decimal for reporting. 

Evaluation System: 

 Basis for awarding marks for class participation and attendance will be as follows: 

Attendance 

Marks 

90%  and above 

10 

85% to 89% 

9 

80% to 84% 

8 

75% to 79% 

7 

70% to 74% 

6 

65% to 69% 

5 

60% to 14% 

4 

Less than 60% 

0 

A student is required to attend at least 60% of all classes held in every course. 

Class Test: The number of class tests of a course shall be at least 2 (Two) for all types of the courses. Evaluation of the performance in the class test will be on the basis of the ‘best one’ of class tests. Class tests should be held regularly every 3 to 4 weeks after starting of class. Duration of each class test shall be 30 minutes. For the convenience of conducting the class tests, a 50 minutes slot should be kept at the beginning of at least 4 working days in a week. The dates for the class tests shall be fixed by the course coordinator/chief course coordinator and shall be announced accordingly. All class tests shall be of equal value. The result of each individual class test shall be posted to the display board for information of the students before the next class test is held. The final computed marks sheet of the Class Tests and Class Attendance shall be submitted in 2 (two) separate sealed envelopes by the course teacher to the Chairman of concerned Examination Committee before preparatory leave for Term final starts. The third copy of the mark sheet along with answer scripts of all the Class Tests should be sent to the Controller of Examinations. 

Mid-Term Exam: 
There shall be 1.5 hours (90 minutes) mid-term examination held regularly every 7 weeks after starting of class. 
Practical Final: 
Course Teacher, Respective Head of the Department will conduct Practical Final Examination. It will be completed in the last 02 (two) weeks before the preparatory leave starts. 
Project and Thesis: 

40% marks for Continuous Assessment to be evaluated by the respective Supervisor. 
60% marks for final examination to be evaluated by the Project Evaluation Committee consisting of all the Head of the Departments & Project Supervisor. 

Comprehensive Viva: 

For All subjects (100% marks): Comprehensive Viva board will be formed with teachers including all Head of the Departments. 
Term Final Examination 

Duration of Term final Examination: 

There shall be 2 (two) hours examination for 2 (two) and 3 credits theory courses. 
Registration System: Students are required to complete their registration formalities before a semester starts. A student has to register in-person. The student information division shall notify the newly admitted students about the time and place of their registration. Students should consult their advisors for planning their courses and to be familiar with IUS policies and procedures related to registration. 
Course Withdrawal 

The courses, which are withdrawn by a student due to some valid reasons. 
It is defined by ‘W’. The grade W (Withdrawal) is also assigned when a student officially drops/withdraws course(s) within the date mentioned in the academic calendar for the semester. 
Incomplete (I) courses 
If a student does not register any offered course of a regular semester, then this course is defined as “incomplete course” and he/she can register this course when offered by the department in the subsequent semesters. 
Retake 

If a student fails in either Supplementary Examination or he/she does not attend in Supplementary Examination on a course, then he/she can register this course with the regular offered courses of a semester as a Retake course. 

If any student does not appear both in Mid-Semester Examination and Semester Final Examination on any course, then he/she cannot register the course for supplementary examination; but he/she can register this course with the regular offered courses of a semester as a Retake course. 

If any student does not attend classes without withdrawal within the time limit (normally up to the time of drop of a course from any semester) will be given the grade “F” in the course and can register as Retake courses. 
All the Retake courses are of grade “F” and are denoted by “R” 


Grade Improvement: 
If a student wishes to re-register a course of earned grade below B+ (B plus) to improve the grade then the course is defined as “Improvement Course” and is abbreviated by “IM”. 

Dropout: 
If any student does not attend classes without withdrawal within the time limit (normally up to the time of drop of a course from any two semesters) will be counted as drop out from the student list. 

 

  

 

 

Image