University of Scholars  +88 01844 075 476  40, Kemal Ataturk Ave, Banani, Dhaka1213
Details of the Offered Courses
B.Sc. in Computer Science & Engineering
Course Code: CSE 12130613 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 problemsolving 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: ifelse, switch case, ternary operator, break, code examples
Loop: For loop, while loop, dowhile 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 12140613 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 problemsolving skills to program design and development.
Laboratory Tasks:
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 11120531 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 evidencebased 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, Lechatelier 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 AtomsFocused Approach, Third Edition, Thomas R Gilbert, Rein V Kirss, Natalie Foster and Stacey Lowery Bretz. 
Course Code: CHE 11120532 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:
Volumetric Analysis:
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: MATH11110541 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 coordinate 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. Coordinate Geometry (two & three dimensions) with Vector Analysis, 12thed, S. Bhattacharjee, Dhaka 

6 
Bell, J. T. 1944. A Treatise on 3Dimensional Geometry, 3rded, S.G. W. M., New Delhi 
Course Code: PHY11110533 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 biprism, 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 Nslits, 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 mediumStokes’ 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 (PartI)” 
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” 2^{nd }ed. B. Lal and N. Subrahmanyam, "Properties of Matter." 
Course Code: 11120533 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:
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 valueofmoney, 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 FunctionsManagerial RolesManagement Skills, Contributing Discipline to OB FieldChallenges 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 shortterm and longterm objectives setting financial objectives setting strategic objectives crafting a strategy executing the strategy evaluating performance and initiating corrective adjustments
Values, Attitudes & Job Satisfaction: ValuesTypes of ValuesValues, Loyalty, and Ethical BehaviorHofstede’s Framework for Assessing Cultures, AttitudesTypes of AttitudesThe Theory of Cognitive DissonanceSelfPerception Theory, Job SatisfactionThe Effect of Job Satisfaction on Employee PerformanceHow Employees Can Express Dissatisfaction.
Personality & Emotions: PersonalityPersonality TraitsThe MyersBriggs Type Indicator, Major Personality Attributes Influencing OB. Emotions Meaning of Emotions & Mood, Differences between Emotion & Mood, Why Emotions Were Ignored in OBEmotion DimensionsOB 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 SmallGroup Networks Grapevine ComputerAided 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: DefinitionTypesApproaches/Theories of Leadership, Approaches/Theories of Leadership.
Organizational Culture: Organizational CultureImportanceCharacteristics, Keeping Culture Alive Stages in the Socialization Process.
Power & Politics: A Definition of PowerLeadership and PowerBases of PowerPower Tactics, Power in GroupsPower in ActionEmployee Responses to Organizational PoliticsImpression Management.
Conflict & Negotiation: ConflictTypes of ConflictComponents 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 FiveStage Model, PunctuatedEquilibrium 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 decisionmaking 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, 13^{th} edition, PrenticeHall. 
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. NurEAlam Siddique. Organizational Behavior. Latest Edition. 

4 
1. Fred Luthans, Organizational Behavior, 12^{th} edition, McGraw Hill. 
Course Code: HUM 11130222 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 socioeconomic, political, environmental and developmental issues that have arisen during this period, before assessing the progress over time. Course Contents:
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: ENG12130231 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 reallife 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:
Course Learning Outcomes (CLOs):
After completing this course, students would be able to:
CLO1: Identify and adapt different techniques of reading academic and nonacademic 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: MATH12130541 Course Title: Mathematics II Course Type: Theory Prerequisite: MATH 11110541 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, GramSchmidt 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:

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 21420613
Course Title: Object Oriented Programming Language Lab
Course Type: Lab
Prerequisite: CSE 12130613
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 12110714
Course Title: Electrical Circuit Analysis
Course Type: Theory
Prerequisite: PHY11110533
Credits: 3
Contact Hours: 42
Total Marks: 10
Course Code: EEE 12110714
Course Title: Electrical Circuit Analysis
Course Type: Theory
Prerequisite: PHY11110533
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, Seriesparallel resistance circuits and their equivalents, Voltage and current divider circuits, DeltaWye equivalent circuits.
Techniques of general DC circuit analysis: Nodevoltage method, Meshcurrent method, Source transformations. Thevenin and Norton equivalents, Maximum power transfer. Superposition technique. Properties of Inductances and capacitances. Seriesparallel 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 singlephase 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 12120714
Course Title: Electrical Circuit Analysis Lab
Course Type: Lab
Prerequisite: PHY11110533
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 3phase system with a balanced load.
Exp11: Verification of selfinductance 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 12360611
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 InclusionExclusion, 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 PigeonHole 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 FirstOrder Recurrences Using Back Substitution, Fibonacci Recurrence Relation, Divide and Conquer Paradigm, Binary Search, Merge Sort, Multiplication of nBit Numbers, DivideandConquer 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 nonlinear 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, EastWest 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:
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/ImpressAudienceProfessionalPresentationSkillsebook/dp/B08D762XRV. Printed 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/powerfulpresentationsconnect1 

3) A Speaker’s Guidebook by Dan O’Hair, Rob Stewart, and Hannah. 6th Edition. 
Course Code: MATH21150541
Course Title: MathematicsIII
Course Type: Theory
Prerequisite: MATH 12030541
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 nonlinear 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, McGrawHill, NY. 

5 

Spiegel, M R. 1974. Fourier Analysis 1sted, McGrawHill Co., New Delhi. 

6 
Spiegel, M R. 1995. Laplace Transforms, 1sted, McGrawHill Co., New Delhi 
Course Code: EEE 21130714
Course Title: Electronic Devices & Circuit
Course Type: Theory
Prerequisite: EEE12110714
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 daytoday life applications.
Course Content:
PN junction as a circuit element: Intrinsic and extrinsic semiconductors, operational principle of pn junction diode, currentvoltage 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.
MetalOxideSemiconductor FieldEffectTransistor (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 opamp circuits. Opamp applications: inverting amplifier, noninverting 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 nonlinear wave shaping, Clipping and Clamping circuits, NonLinear function circuits. Negative resistance switching circuits. Timing circuits; Bistable, monostable 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 Opamps.
CLO2: Compare the different characteristics of diodes, transistors, MOSFET and opamp.
CLO3: Analyze the performance of those devices and its biasing circuits.
CLO4: Solve realworld 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 21140714
Course Title: Electronic Devices & Circuits Lab
Course Type: Lab
Prerequisite: EEE12120714
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: IV 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 Opamp.
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 11110611
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 uptodate 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 


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

Course Code: CSE 11120611
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 handson use.
CLO3: Able to learn a handful of various fundamental concepts of programming language, compiler and interpreter.
CLO4: Able to understand the fundamental concept of networking, security system, cybercrime and ethical issues.
Course Code: CSE 2121–0613
Course Title: System Analysis and Design
Course Type: Theory
Pe requisite: CSE 12130613
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 objectoriented 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; Humancomputer 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 decisionmaking 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 21220613
Course Title: System Analysis and Design Lab
Course Type: Lab
Pe requisite: CSE 12140613
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 eventdriven 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 wellorganized, 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: CE21440611
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/chapter1/
https://gencor.in/autocadsyllabus/

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, PrenticeHall of India, 1995. 

Course Code: CSE 21050613
Course Title: Competitive ProgrammingI
Course Type: Lab
Prerequisite: CSE 11110613, CSE 12130613Credits: 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 problemsolving process, one can manifest their language skill as well as efficient use of syntax and grapes a reallife experience of programming.
Course Content:
Introduction to Competitive Programming: History and background, Different problemsolving platforms, Languages, Tools for problemsolving, Career path
Data types and InputOutput: 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 problemsolving skills.
CLO3: Able to analyze time and space complexity and optimize code, demonstrate problemsolving 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 22110414
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 22170542
Course Title: Probability & Statistics
Course Type: Theory
Prerequisite: MATH 12130541
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 nonprobability sampling, simple random sampling, stratified sampling, cluster sampling, systematic sampling, sampling error, nonsampling 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. McGrawHill. 

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 22150613
Course Title: Data Structure and Algorithm
Course Type: Theory
Prerequisite: CSE 11110613, CSE 12360611
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 benchmark 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 multidimensional 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 singlelinked, doublylinked, and circular lists
Methodology of Analysis:
Asymptotic Notation, Best Case, Worst Case, Average Case, Solving Recurrence Equations,
Single and multidimensional 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 singlelinked, doublylinked, 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, ONotation, 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,Dequeue, 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 heightbalanced trees (AVL). Application of Graph and Trees.
Heaps:
Introduction to heap as a data structure. analysis of insert, extractmin/max and deletemin/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 FloydWarshall, 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 22160613
Course Title: Data Structures and Algorithm Lab
Course Type: Lab
Prerequisite: Prerequisite: CSE 11110613, CSE 12360611
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 FloydWarshall 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 onedimensional 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 nonlinear 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 22340613
Course Title: Numerical Methods with MATLAB
Course Type: Criminoloty
Prerequisite: MATH 11110541, CSE 11110613
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.
Nonlinear Equations: Roots of Nonlinear Equations, Bracketing MethodBisection Method, Bracketing Methodfalse position method, MATLAB Program of Bisection & False Position Method, Open MethodFixed Point Iteration, Open Method Newton Raphson Method & Secant Method, MATLAB Program of Newton Raphson and Secant Method.
Linear Equation: NaiveGauss, Gauss Partial Pivoting, GaussJordan Elimination, MATLAB Program of NaiveGauss ELimination.
Linear Algebraic Equations: GaussSeidel iteration Method, MATLAB Program of GaussSeidel Elimination.
Curve Fitting: InterpolationNewton’s Divided Difference Formula, MATLAB Program of InterpolationNewton’s Divided Difference Formula, RegressionPolynomial, Least Square, Linear and NonLinear 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, RungeKutta Method.
Course Learning Outcomes (CLOs)
CLO1: Students will be able to understand the basics numerical concepts with linear/ nonlinear/ 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 22050613
Course Title: Competitive ProgrammingII
Course Type: Lab
prerequisite: CSE 21050613
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
Warmup 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 contestI
Dynamic array: Vector, list, pointer, iterator
Set, multiset
Stack, Queue
Map: Ordered map, unordered_map
Advanced contestII
Number theory: Prime number and time complexity optimization, sieve of Eratosthenes, Prime factorization, GCD, LCM
Advanced contestIII
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 reallife problemsolving
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 31510714
Course Title: Digital Logic Design
Course Type: Theory
prerequisite: EEE 12110714
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.
Flipflops: SR, JK, Master slave, T and D type flipflops and their characteristic tables & equations; Triggering of flipflops, 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 multivariable Karnaugh map methods.
CLO3: Able to identify and diagnose the small scale combinational circuits: arithmetic logic units, adder, subtractor, encoders, decoders, multiplexers, demultiplexers
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 31520714
Course Title: Digital Logic Design Lab
Course Type: Lab
prerequisite: EEE 12120714
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 problemsolving 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 (KMap)
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 FlipFlop.
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 reallife projects and correlate with the given problem.
Course Code: CSE 31430611
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, NonDeterministic 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, NonDeterministic 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 realworld 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 McGrawHill, 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
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, whistleblowing, 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; interprofessional 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 interprofessional relationships within the organization and outside of the organization.
Course Code: GED 31150411
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 31310612
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, multilayer 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, VlanVTP, 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 webbased 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 routing, Multiple access protocol: Standards IEEE 802.*, IPV4, IPV6, ARP, RARP , IP address and IP subnetting, Data link control, Link layer and services, Error detection and Correction
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 subaddress 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: McGrawHill. 
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 TopDown Approach, Published by AddisonWesley, 6th Edition. 

4 
Andrew S. Tanenbaum and David J. Wetheral, Computer Networks, Published by Prentice Hall, 5th Edition. 

Course Code: CSE 31320612
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:
Indepth 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 31080613
Course Title: Integrated Design Project I
Type: Lab
prerequisite: CSE 21210613, CSE 12140613
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 toplevel 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 32190613
Course Title: Compiler Construction
Course Type: Theory
prerequisite: CSE 11110613
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, PreComputed Parsing Table, Test Driven Parsing Algorithm, Bottom up Parsing, Handle, ShiftReduce 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 32200613
Course Title: Compiler Construction Lab
Course Type: Lab
prerequisite: 11120613
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 highlevel 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 32230612
Course Title: Database Management System
Course Type: Theory
prerequisite: CSE 12140613
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 inmemory 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 Multiuser 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.
FactFinding Techniques: What facts are collected, Techniques, A worked example
EntityRelationship Modeling: Semantic Data Models, Introduction to EntityRelationship Data Model Different Constructs of ER Data Model, Abstraction Process Modeling different types of Entities and Attributes. Cardinality and Degree of a Relationship, Unary, Binary and narray Relationships.
EntityRelationship 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, BoyceCodd 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 McGrawHill, 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 32240612
Course Title: Database Management System Lab
Course Type: Lab
prerequisite: CSE 11120613
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 handson experience by creating a realworld ecommerce 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 ER 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 highlevel 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 McGrawHill, 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 32240612
Course Title: Database Management System Lab
Course Type: Lab prerequisite: CSE 11120613
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 handson experience by creating a realworld ecommerce 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 ER 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 highlevel 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 ZiffDavis Press, Illustrated Edition. 

Course Code: CSE 32540714
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 midlevel 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 part2 and procedures
Programming with Procedures part2 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 midlevel 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 32460613
Course Title: Web Programming
Course Type: Theory
Prerequisite: CSE 21210613, CSE 3223, CSE 12140613
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 fullstack 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 IfElse, 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 markup 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 Gitbased 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 wellstructured, readily maintainable, standardscompliant 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 clientside 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 32080613
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 teammember 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 41250613
Course Title: Software Engineering
Course Type: Theory
Prerequisite: CSE 21210613, 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 objectoriented technology via the Use Case Model and the ObjectOriented Model. Students will be introduced to various software process models, project management, software requirements and design as a problemsolving 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, Vmodel, Incremental Model, Agile Model, Iterative Model, BigBang 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, EntityRelationship 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, GoelOkumoto (GO) Model, MusaOkumoto 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, AddisonWesley, 2011 

3 
Software Engineering by Ivan Marsic 

4 
Software Engineering: Principles and Practice by Hans van Vliet 

Course Code: CSE 41260613
Course Title: Software Engineering Lab
Course Type: Lab
Prerequisite: CSE 21220613, 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 : Statechart 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 41350612
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 41480723
Course Title: Mobile Application Development
Course Type: Lab
prerequisite: CSE 12140613, 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 41370613
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 massstorage 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 41380613
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 massstorage 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 41990613
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 neckdeep 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 multidisciplinary and multicultural teams.
CLO4: Able to improvise the capability to undertake lifelong learning by analyzing real world situations.
Course Code: CSE 42990613
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 neckdeep 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 multidisciplinary and multicultural teams.
CLO4: Able to improvise the capability to undertake lifelong learning by analyzing real world situations.
Course Code: CSE 42010612
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 Preprocessing: 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, Backpropagation algorithm, Support Vector Machine (SVM, Kernel functions.
Model Evaluation: Holdout Method, Random Sub Sampling, CrossValidation, evaluation metrics, confusion matrix.
Association Rule: Transaction dataset, 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, Kmeans: The Basic Kmeans Algorithm, Strengths and Weaknesses of Kmeans 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, overfitting, regularization. performance evaluation metrics, validation methods.
Recommended Datasets for Practical
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. PrenticeHall of India 

7 
Pujari, A. (2008). Data Mining Techniques. 2nd edition. University Press. 

Course Code: CSE 42290613
Course Title: Artificial Intelligence
Course Type: Theory
prerequisite: CSE 11110613
Credits: 3
Contact Hours: 42
Total Marks: 100
Year/Level: 4
Semester/Term: 2
Rationale:
Artificial intelligence is a fastmoving 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, NQueens 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, SemiSupervised 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 humancentered problems.
CLO4: Competent to apply knowledge representation, reasoning, and demonstrate practical experience by experimenting realworld 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 42300613
Course Title: Artificial Intelligence Lab
Course Type: Lab
prerequisite: CSE 11120613
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 ReadWrite Problem demonstration in Prolog
Finding Ancestor and Family Tree investigation problem in Prolog.
Classic AI searching problem demonstration using 8Puzzle 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 αꞵ 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 41630613
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 highlevel project overview, task management, reporting and time tracking. The project management is to bring about beneficial change or added value repetitive, permanent, or semipermanent 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 41490612
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, scikitlearn, 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 splitapplycombine, 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
Practical :
NumPy and arraybased practicals
Experiments with Pandas Data Structures
Data Loading, Storage, and File Formats Practica
Practicals based on Web API Interaction
Data Cleaning and PreparationBased Practicals
Data WranglingBased Practicals
Practicals based on Matplotlib Data Visualization
Data AggregationBased 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.

2 
O’Neil, C., & Schutt, R. (2013). Doing Data Science: Straight Talk from the Frontline O’Reilly Media 

Course Code: CSE 41640613
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 graphtheoretic 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 problemsolving, 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 PrenticeHall of India Pvt Ltd.

Journals, Web Materials, etc. 
2 
Douglas B. West, Introduction to Graph Theory, Published by Pearson, 2nd Edition. 

Course Code: CSE 41720714
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 IoTspecific data processing and analytics frameworks. Handson 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 41710613
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: Multitenancy, Massive Scalability, Elasticity
InfrastructureasaService(IaaS): Introduction to IaaS, Resource, Virtualization, Case Studies
PlatformasaService(PaaS): Introduction to PaaS, Cloud Platform, Management of Computation and Storage, Case Studies.
SoftwareasaService(SaaS): Introduction to SaaS, Web Services, Web 2.0, Web OS, Case Studies.
Cloud Issues and Challenges: Cloud Provider Lockin or Vendor Lockin, 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 41680613
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 highthroughput 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 Structures: Protein 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 41690714
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, DenavitHartenberg 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, EulerLagrange formulation, joint and Cartesian forces, Equations of motion using EulerLagrange 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 41730611
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 42770612
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 handson experience necessary to design, install, and configure personal computers, peertopeer networks, and clientserver 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 peertopeer 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 clientserver 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 AddisonWesley Professional.

Journals, Web Materials, etc. 
2 
AnandaDeveriva, Network Administrators Survival Guide, published by Cisco Press.


Course Code: CSE 42780612
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 handson 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 Windowsbased LAN
CLO3: Can evaluate troubleshooting alternatives.
Course Code: CSE 42270613
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, Videodisplay 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 LineDrawing Algorithm, Bresenham’s Circle Algorithm ,Ellipse Generating Algorithm, Midpoint circle and ellipse algorithms.
Filled area primitives: Clipping and Viewport, Flood Fill Algorithm, Boundary Fill Algorithm, ScanLine Polygon Fill Algorithm.
2D Transformations: Introduction of Transformation, Translation, Scaling, Rotation, Reflection, Shearing, Matrix Representation, Homogeneous Coordinates, Composite Transformation, Pivot Point Rotation.
2DViewing: The Viewing Pipeline, Viewing Coordinate Reference Frame, Window to Viewport Coordinate Transformation, 2D Viewing Functions.
Clipping Techniques: Clipping, Point Clipping, Line Clipping, Midpoint Subdivision Algorithm, Text Clipping, Polygon, SutherlandHodgeman Polygon Clipping, WeilerAtherton Polygon Clipping.
3D Geometric transformations: Translation, rotation, scaling, reflection and shear transformations, composite transformations.
3D 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 McGrawHill, 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 42280613
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 MidPoint 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 CohenSutherland 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 42790612
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: FrequencyReuse Principle, Transmitting, Receiving, Roaming, First Generation, Second Generation, Third Generation
Cellular Telephone: GSM, IS95, 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 42800612
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 handson learning on wireless communication and indepth knowledge of Matlab.
Course Outlines:
Introduction to Matlab, Install and overview
Syntax and library functions of Matlab, problemsolving with Matlab
Plot, subplot, and graphical visualization with Matlab
Frequencies, phase, sin waveform, cos waveform
Amplitude modulation
Phase modulation
Amplitudeshift keying (ASK)
➢ Frequencyshift 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 42810613
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 mediumsized 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, CostBenefit 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 Nonfunctional 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 42820613
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 UseCase 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 42830612
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: Multidatabases, 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 42840612
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 reallife 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 TermI and TermII 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 Classteaching, Open discussion, Academic tasks etc.
Practical/Sessional Courses: Includes Laboratory experiment/Field Work etc.
Project and Thesis: During the LevelIV 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 4years 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 



(i) Class Attendance 
: 15% 
(ii) Class Test/Quiz 
: 15% 
(iii) Assignment/Presentation 
: 20% 

: 20% 
(c) Term Final Exam 
: 30% 
Total 
: 100% 
Practical/Sessional/Lab 



(i) Class Attendance 
: 10% 
(ii) Performance 
: 30% 
Total 
: 40% 


(i) Experiment 
: 20% 
(ii) Report 
: 20% 
(iii) VivaVoce 
: 20% 
Total 
: 60% 


Project or Thesis 


: 40% 

: 60% 
Total 
: 100% 
Comprehensive Viva
All subject’s 100%
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.
MidTerm Exam:
There shall be 1.5 hours (90 minutes) midterm 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 inperson. 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 MidSemester 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 reregister 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.
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