Syllabus for
Bachelor of Technology (Computer Science and Engineering)
Academic Year  (2024)

Course objectives: 

●      To study the switching theory and the realization of logic gates.

●      To study minimization methods.

●      To study combinational circuits.

• To study sequential circuits

Switching Theory: Laws of Boolean algebra, Theorems of Boolean algebra, Switching functions, Methods for specification of switching functions - Truth tables and Algebraic forms, Realization of  functions using logic gates. Digital Logic Elements: Electronic logic gates, Positive and negative logic, Logic families -TTL, ECL and CMOS, Realization of logic gates

Simplification of Boolean Expressions and Functions: Algebraic methods,     Canonical forms of Boolean functions, Minimization of functions using Karnaugh     maps, Minimization of functions using Quine-McClusky method

Design of Combinational Logic Circuits: Gate level design of Small Scale     Integration (SSI) circuits, Modular combinational logic elements - Decoders,     Encoders, Priority encoders, Multiplexers and Demultiplexers. Design of Integer     Arithmetic Circuits using Combinational Logic: Integer adders - Ripple carry adder     and Carry look ahead adder, Integer subtractors using adders, Unsigned integer     multipliers - Combinational array circuits, Signed integer multipliers - Booth's     coding, Bit-pair recoding, Carry save addition and Wallace tree multiplier, Signed     integer division circuits - Combinational array circuits, Complexity and propagation     delay analysis of circuits. Design of Combinational Circuits using Programmable     Logic Devices (PLDs): Programmable Read Only Memories (PROMs),     Programmable Logic Arrays (PLAs), Programmable Array Logic (PAL) devices,     Design of multiple output circuits using PLDs

Sequential Circuit Elements: Latches -RS latch and JK latch, Flip-flops-RS, JK, T     and D flip flops, Master-slave flip flops, Edge-triggered flip-flops. Analysis and     Design of Synchronous Sequential Circuits: Models of sequential circuits - Moore     machine and Mealy machine, Flip-flops - Characteristic table, Characteristic     equation and Excitation table, Analysis of sequential circuits- Flipflop input     expressions, Next state equations, Next state maps, State table and State transition     diagram, Design of sequential circuits - State transition diagram, State table, Next     state maps, Output maps, Expressions for flip-flop inputs and Expressions for circuit     outputs, Modular sequential logic circuits- Shift registers, Registers, Counters and  Random access memories, Design using programmable logic sequencers (PLSs).     Design of Arithmetic Circuits using Sequential Logic : Serial adder for integers,     Unsigned integer multiplier, Unsigned integer division circuits, Signed integer     division, Floating-pint adder/subtractor - Design of control circuit, Floating - point     multiplier

Case study: Learn the Fundamentals of Digital Logic Design with VHDL Informal Laboratory: Design and implementation of binary adder / subtractor using basic gates

Design and implementation of applications using multiplexers

Design and implementation of Synchronous & Asynchronous Counters

Design and implementation of Shift Registers

Coding Combinational Circuits using Hardware Description Language (HDL)

R2. R D Sudhaker Samuel, “Illustrative Approach to Logic Design. Sanguine-Pearson”, 2010.

R3. Charles H. Roth, “Fundamentals of Logic Design”, Cengage Learning, 5th Edition, 2004.

R4. Ronald J. Tocci, Neal S. Widmer. Gregory L. Moss, “Digital Systems Principles and     Applications, ” 10th Edition. Pearson Education, 2007

R5. TM Morris Mano, “Digital Logic and Computer Design”, Pearson Education, 10th Edition, 2008

•       CIA 1 – 20 Marks

•       CIA 2 – 50 Marks

•       CIA 3 – 20 Marks

•       End Semester Examination – 100 Marks

•       Attendance – 5 Marks

(Scaled: CIA – 50 Marks & ESE – 50 Marks)

Course Description:

This course will discuss the basic concepts of computer architecture and organization that can help the students to learn the fundamental elements in a computer system including the processor, memory, and interfaces to external components and systems. Also, students can have a clear view as to how a computer system works. Examples and illustrations will be mostly based on a popular MIPS architecture.

 Course Objective:

1. To have a thorough understanding of the basic structure and operation of a digital computer.
2. To discuss in detail the operation of the arithmetic unit including the algorithms & implementation of fixed-point and floating-point addition, subtraction, multiplication & division.
3. To study in detail the different types of control and the concept of pipelining.
4. To study the hierarchical memory system including cache memories and virtual memory. 
5. To study the different ways of communicating with I/O devices and standard I/O interfaces.

Functional Units – Basic Operational Concepts – Performance – Instructions: Language of the Computer – Operations, Operands – Instruction representation – Logical operations – decision making – MIPS Addressing.

Addition and Subtraction – Multiplication – Division – Floating Point Representation – Floating Point Operations

A Basic MIPS implementation – Building a Datapath – Control Implementation Scheme – Pipelining – Pipelined data path and control – Handling Data Hazards & Control Hazards – Exceptions

Parallel processing challenges – Flynn’s classification – SISD, MIMD, SIMD, SPMD, and Vector Architectures - Hardware multithreading – multi-core processors and other Shared Memory Multiprocessors - Introduction to Graphics Processing Units, Clusters, Warehouse Scale Computers and other Message-Passing Multiprocessors.

Memory Hierarchy - memory technologies – cache memory – measuring and improving cache performance – virtual memory, TLB‗s – Accessing I/O Devices – Interrupts – Direct Memory Access – Bus structure – Bus operation – Arbitration – Interface circuits – USB

 T2.Carl Hamacher, ZvonkoVranesic, SafwatZaky and NaraigManjikian, “Computer Organization and Embedded Systems”, Sixth Edition, Tata McGraw Hill, 2012.

R2.John L. Hennessey and David A. Patterson, “Computer Architecture – A Quantitative Approach”, Fifth Edition, Morgan Kaufmann / Elsevier Publishers, 2012

(Scaled: CIA – 50 Marks & ESE – 50 Marks)

This course provides knowledge on Stacks, Queues, Linked Lists, Trees and Heap. The knowledge of C language and data structures will be reinforced by practical exercises during the course of study. The course will help students to develop the capability to select and design data structures for algorithms that are appropriate for problems that they might encounter. 

1. Understand, Practice and Assimilate fundamentals of data structures and their applications essential for programming/problem solving.
2. Describe, Apply and Design the Linear Data Structures: Stack, Queues, Lists.
3. Describe, Apply and Design  the Non-Linear Data Structures such as Trees and Graphs
4. Identify appropriate data structure during program development/Problem Solving

The Abstract Data Type, Model for an Abstract Data Type,Data Structure Definition, Classification   of data structures, Operations on data structures, Stack ADT: Definition, Array Implementation of stack, Operations on stack, Stack Applications-Conversion of expression, Evaluation of postfix expression.

Experiment 1: Develop and Implement a menu driven Program in C for the different operations on STACK.

Experiment 2: Develop and Implement a Program in C for the Stack Applications.

The Queue ADT: Definition, Array Implementation of queue, Types of queues: Simple queue, Circular queue, Double ended queue (de -queue), Operations on all types of Queues, Priority Queues, Applications of Queues.

Experiment 3: Develop and Implement a menu driven Program in C for the different   operations on Linear QUEUE ADT.

Experiment 4: Develop and Implement a menu driven Program in C for the different  operations on Circular QUEUE

The List ADT: Singly linked list implementation, Double linked list implementation, insertion, deletion and searching operations on all List implementation, Concepts of Circular linked list, Array implementation of Lists, Implementation of stacks and queues using Single Linked List, Applications of linked list.

Experiment 5: Develop and Implement a menu driven Program in C for the different operations on Singly Linked List (SLL).

Experiment 6: Develop and Implement a menu driven Program in C for the different operations on Doubly Linked List (DLL).

Preliminaries, Binary Trees, Tree Traversals, Binary Search Trees, AVL Trees, Splay trees, B-Tree, Expression tree, Heaps ADT- Binary Heap, Application of Trees.

Experiment 7: Develop and Implement a menu driven Program in C for the different operations on Binary Search Tree (BST).

Experiment 8: Develop and Implement a program in C to create a max heap/Min heap.

Introduction to Graphs, Graph Traversals-DFS, BFS, Minimum Spanning Tree – Prim’s and Kruskal's Algorithm, Single -Source Shortest Paths– Bellman-Ford algorithm and Dijkstra’s Algorithm, Applications of Graphs

Experiment 9: Develop and Implement Minimum spanning tree using Prims Algorithm.

Experiment 10: Develop and Implement Single source shortest path using Dijkstra’s Algorithm.

R2. Data Structures: A Pseudocode approach with C, Richard F. Gilberg and Behrouz A, Forouzan, Thomson, Second Edition,2016.

(Scaled: CIA (Theory + Practical) –  70  Marks & ESE – 30 Marks)

Course Description

Through practical exercises and project-based learning, students will develop critical thinking, problem-solving, collaboration skills, and the ability to learn how to learn. In addition, they will gain highly sought-after skills in Java programming, database connectivity, and web development, which are essential for employability as Java developers, as well as learning how to identify and develop ideas for Java-based applications that can be turned into successful businesses. Furthermore, the course will cover cross-cutting needs such as ethics, sustainability, and inclusivity in software development to ensure that students can develop responsible and sustainable applications.

Course Objectives:

1.  Software development in business environments has become more sophisticated, the software implementation is becoming increasingly complex and requires the best programming paradigm which helps to eliminate complexity of large projects.

2.  Object Oriented Programming (OOP) has become the predominant technique for writing software at present. Many other important software development techniques are based upon the fundamental ideas captured by object-oriented programming.

3. The course also caters to the understanding of event driven programming, generic programming and concurrent programming.

Java History-JavaVirtual Machine, Command Line Arguments, - Elements of Java Language- Introduction to objects, Classes – Attributes and methods – Simple classes Circle,Employee,Student etc.-Control structures – If structure – nested if – break – Labeled break – switch structure - Loop Structures – For – While  – Do while – Nested.

Overview of Object oriented Program-Classes and Objects–Constructors – Multiple constructors-Encapsulation and access modifiers,Overriding - Inheritance and polymorphism, - Real life examples of polymorphism and inheritance -Abstract classes and Interfaces.

Exception Handling and Packages:   Handling exceptions with try-catch blocks, Creating custom exceptions, Handling checked and unchecked exceptions, Finally  blocks.  Defining  Package,  CLASSPATH,  Importing  Packages. Generic Programming: Generic Classes – Generic Methods.

Introduction to Multithreading and Concurrency:  Understanding Threads and Processes,Creating Threads,Thread States,Thread Scheduling, Synchronization -using Locks.   Deadlocks and their Prevention,Thread Communication using wait(), notify(), and notifyAll() methods.

Graphical User Interfaces–Windows and Frames – AWT Graphics class – Introduction  to Swing–SwingComponents-Creating windows with buttons, labels,  checkbox,  choice,  text  area,  textbox  etc.-Event handling and Layout Management.

T1.  C.  Xavier,  Object  Oriented  Programming  Paradigm  with  JAVA,  New  Age

International Publishers, INDIA, (2024)

T2.    Herbert  Schildt,  "Java:  The  Complete  Reference"  by,  12th   edition,  McGraw

Hill(2021)

CIA 2 – 50 Marks

CIA 3 – 20 Marks

Practical – 50 Marks

End Semester Examination – 100 Marks

Attendance – 5 Marks

(Scaled: CIA (Theory + Practical) –  70  Marks & ESE – 30 Marks)

Course Description:

The course covers contents from basics of XR(AR-VR-MR), Unity Basic concepts, Introductory concepts of C# programming, functions of Augmented Reality.

Course objectives:

Students should be able to:

● Understand the core concepts and applications of Extended Reality (XR).

● Navigate and utilize the Unity platform proficiently for XR development.

● Develop XR experiences using C# scripting for interactive elements.

● Create Augmented Reality (AR) applications and Virtual/Mixed Reality (VR/MR) environments.

• Design and implement immersive user interfaces tailored for XR applications.

Introduction to immersive technologies and environments, XR hardwares, XR softwares, Design principles ,Computer graphics, UI and UX, Applications and benefits of immersive tech.

Unity ID creation and login, Unity interface basics: Creating a scene in unity, importing 3d models: Lighting. 3D Animations in unity , Basic mechanisms(physics and non physics) , Audio and effects , User interface, Buttons.

Data types, variables and operators.Control structures: If statements and loops. Classes, objects and methods, Using functions to add properties to objects in the scene,changing colors  via  scripts  and  UI,switching  between  scenes.

Introduction to AR basics, Plane tracking, AR Foundation, ARCore/ARKit,Building AR experiences.

Setup for VR/MR in unity. Creating and configuring scenes, Using “Building Blocks” from meta for setting up interaction. UI/UX in VR:MR. Using depth sensors and modal features for mixed reality.

https://learn.unity.com/pathway/unity-essentials

https://learn.unity.com/pathway/mobile-ar- development

https://learn.unity.com/pathway/vr-development

ESE: 50 Marks

(Scaled CIA 25 Marks and ESE 25 Marks)

Course Description:

This course is the prerequisite for advanced courses like Machine Learning, Deep Learning, Natural Language 

Processing (NLP), etc. This course also provides knowledge and skills to the students to analyze and classify 

various kinds of data readily available on the internet. 

Course Objective:

1. Discuss the core concepts of Statistical Analytics and Data manipulation

2. Apply the basic principles, models, and algorithms of supervised and unsupervised learning

mechanisms.

3. Analyze the structures and algorithms of regression methods

4. Explain notions and theories associated with Convolutional Neural Networks

5. Solve problems in High-Dimensional Regression

Knowledge discovery: finding structure in data, Data quality versus data quantity, Statistical modeling versus statistical description. Data types, Data summarization, Means, medians, central tendency, summarizing variation, summarizing (bivariate) correlation, Data diagnostics, data transformation, Outlier analysis, Entropy, Data transformation, Simple smoothing techniques, Binning, Moving averages, Exponential smoothing.

Data visualization, Statistical graphics, and Statistical Inference: Univariate visualization, Strip charts, dot plots, boxplots, stem-and-leaf plots, Histograms and density estimators, Quantile plots, Bivariate and multivariate visualization, Pie charts and bar charts, Multiple boxplots and QQ plots, Scatterplots and bubble plots, Heatmaps, Time series plots, Statistical inference, Parameters and likelihood, Point estimation, Bias, The method of moments, Least squares/weighted least squares, Maximum likelihood.

Interval estimation, Confidence intervals, Single-sample intervals for normal (Gaussian) parameters, Two-sample intervals for normal (Gaussian) parameters, Testing hypotheses, Single-sample tests for normal (Gaussian) parameters, Two-sample tests for normal (Gaussian) parameters, Walds tests, likelihood ratio tests, and ‘exact’ tests, Multiple inferences-the simple linear model, Regression diagnostics, Correlation analysis.

Binary classification via logistic regression, ROC curves, Linear discriminant analysis (LDA), Linear discriminant functions, Bayes discriminant/classification rules, Bayesian classification with normal data, Naïve Bayes classifiers, k-Nearest neighbor classifiers, Treebased methods, Classification trees, Pruning, Boosting, Regression tree.

Techniques for unsupervised learning: dimension reduction, Unsupervised versus supervised learning, Principal component analysis, Principal components, implementing a PCA, Cluster Analysis, Hierarchical Clustering, Partitional clustering-Association rules/market basket analysis, Association rules for binary observations, Measures of rule quality.

T2. Géron, Aurélien. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. O'Reilly Media, 2019.

R2. Fukunaga, Keinosuke. Introduction to statistical pattern recognition. Elsevier, 2013.

R3. Bishop, Christopher M. "Pattern recognition." Machine learning 128, no. 9 (2006).

R4. Ross, Timothy J. Fuzzy logic with engineering applications. John Wiley & Sons, 2005.

CIA 2 – 50 Marks

CIA 3 – 20 Marks

Practical – 50 Marks

End Semester Examination – 100 Marks

Attendance – 5 Marks

(Scaled: CIA (Theory + Practical) –  70  Marks & ESE – 30 Marks)

Course Description: 

This course introduces ethical hacking and penetration testing, focusing on practical techniques and tools ethical hackers use to assess and improve the security of computer systems and networks. 

Course Objective:

1. Understand the ethical hacking methodology and the phases of an attack, including reconnaissance, scanning, enumeration, and exploitation.

2. Develop proficiency in applying ethical hacking techniques and tools to identify security vulnerabilities and assess the security posture of computer systems and networks.

Importance of Security: Threats and Vulnerabilities, Attacks, Security Breaches, Exposure - Elements of Security: Accountability, Reusability The Security, Functionality, and Ease of Use Triangle - Phases of an Attack - Types of Hacker Attacks - Hacktivism - Ethical Hackers - Ethical Considerations. 

Footprinting - Types - Information Gathering Methodology: Unearthing Initial Information, People Searching, Information Gathering Stances - Footprinting Tools.

Introduction - Types - Scanning Methodology: Live Systems, Open Ports, Fingerprint the Operating System, Vulnerabilities Scan, Probe the Network, Anonymous Surfing, Countermeasures - Scanning Tools.

Introduction - Types: User Enumeration, Service Enumeration, Network Enumeration, DNS Enumeration, SNMP Enumeration, OS Enumeration, File System Enumeration, Web Enumeration  - Techniques - Enumeration Tools.

Exploitation and Gaining Access - Cracking Passwords: Types, Password Attacks, Password Guessing, Password Cracking Tools, Countermeasures. Privilege Escalation - Keyloggers and Spyware - Post-Exploitation and Reporting.

T1. James S. Tiller, “The Ethical Hack: A Framework for Business  Value Penetration Testing”, Auerbach Publications, CRC Press. 

T2. EC-Council, “Ethical Hacking and Countermeasures Attack  Phases”, Cengage Learning.

R1. Michael Simpson, Kent Backman, James Corley, “Hands-On  Ethical Hacking and Network Defense”, Cengage Learning.

• CIA 1 – 20 Marks
• CIA 2 – 50 Marks
• CIA 3 – 20 Marks
• Practical – 50 Marks
• End Semester Examination – 100 Marks
• Attendance – 5 Marks

(Scaled: CIA (Theory + Practical) –  70  Marks & ESE – 30 Marks)

Course Description:

This course is an introduction to statistical methods used for data analysis. It is s very structured course to give basic and useful insight to the world of data analytics and provides you the complete package to be comfortable using statistics and analyzing big data.

Course Objectives:

1. To discuss the core concepts Statistical Analytics and Data manipulation.

2. To apply the basic principles, models, and algorithms supervised and unsupervised learning mechanisms.

3. To analyze the use of SVM and Convolution Neural Networks in data science applications.

Knowledge discovery: finding structure in data, Data quality versus data quantity, Statistical modeling versus statistical description. Data types, Data summarization, Means, medians, and central tendency, Summarizing variation, Summarizing (bivariate) correlation, Data diagnostics and data transformation, Outlier analysis, Entropy, Data transformation Simple smoothing techniques, Binning, Moving averages, Exponential smoothing. Introduction to SPSS (IBM’s) statistical tool.

The simple linear model, Multiple inferences and simultaneous confidence bands, Regression diagnostics, Weighted least squares (WLS) regression, Correlation analysis. Unsupervised versus supervised learning, Principal component analysis, Principal components, Implementing a PCA, Exploratory factor analysis.

Projection Pursuit Regression, Neural Networks, Fitting Neural Network, Some Issues in Training Neural Networks, Bayesian Neural Nets, Computational Considerations.

Introduction, The Support Vector Classifier, Support Vector Machines and Kernels, Generalizing Linear Discriminant Analysis, Flexible Discriminant Analysis, Penalized Discriminant Analysis, Mixture Discriminant Analysis.

Definition of Random Forests, Details of Random Forests- Out of Bag Samples, Variable Importance, Proximity Plots; Analysis of Random Forests; Ensemble Learning, Boosting and Regularization Paths, Learning a Good Ensemble, Rule Ensembles.

2. Russell, Stuart J., and Peter Norvig. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,, 2016.

2. Ian Goodfellow and Yoshua Bengio and Aaron Courville,” Deep Learning ”, MIT Press, March 2018.

3. Marcoulides, George A., and Scott L. Hershberger. Multivariate statistical methods: A first course. Psychology Press, 2014.

 (Scaled: CIA (Theory + Practical) –  70  Marks & ESE – 30 Marks)

Course Description:

In this introductory quantum computing course, students will learn the basic concepts of quantum computing and quantum information processing. The course covers the necessary prerequisites in mathematics, quantum mechanics, and computer science as the first module and then moves to quantum bits, quantum gates, quantum circuits, and basic quantum algorithms. The course will involve projects in quantum algorithm development using Python programming. The course concludes with a broad overview of quantum computing applications.

Course Objective:

After completing the course, students should be able to -

•Develop proficiency in linear algebra and complex numbers for quantum information processing

•Understand the principles of quantum mechanics, including wave functions and operators

•Mathematically explain qubit states, operations, multi-qubit systems, Hilbert space

•Mathematically explain superposition and entanglement properties of qubits

•Implement basic quantum gates, including X, Y, Z, Rx, Ry, Rz, Hadamard and CNOT gates

•Design quantum circuits for specific tasks like Binary Adder Circuits

•Understand basic application of superposition, interference, and entanglement in algorithm design

•Explain and reason about Deutsch-Jozsa Algorithm, Bernstein Vazirani Algorithm

•Implement basic quantum gates and quantum algorithms to create a quantum simulator in numpy

•Implement extended versions of basic quantum algorithms from scratch without using libraries

Note: The same objectives will be used in developing assignments, project assessments, and hands-on exercises.

Linear algebra fundamentals, complex numbers, vector spaces, Hilbert Space, eigenvalues and eigenvectors, basics of quantum mechanics, wave functions, probability amplitudes, operators, and observables.

Qubit, Bloch Sphere, Bra Ket notation, Single Qubit State, Composite state, Linear superposition, Basis states, Entanglement between qubits, Density Matrix Form, Quantum Computing Devices, Systems, Software, and Hardware

Mathematics of Quantum Gates, Implementation in devices, Types of Gates, Single Qubit and Multi-qubit Gates, Rotation around angle and axis, Quantum circuit Constructions, Bell state circuits, GHZ state, Quantum Adders

Quantum algorithm design, Use of superposition for quantum parallelism, quantum interference, phase kick-back circuits, classical and quantum algorithms for Deutsch’s problem, Deutsch–Jozsa algorithm, Bernstein–Vazirani algorithm

○ Implement basic quantum gates and quantum algorithms to create a quantum simulator in numpy

○ Implement extended versions of basic quantum algorithms from scratch without using libraries

1. "Quantum Computation and Quantum Information" by Michael A. Nielsen and Isaac L. Chuang.

1. "Quantum Computing: A Gentle Introduction" by Eleanor Rieffel and Wolfgang Polak.

2. "Quantum Information and Computation" by Christopher A. Fuchs, Masahito Hayashi.

End Sem Project : 30 Marks

Final Examination: 40 Marks

CIA: 100 Marks 

ESE: No 

Course Description:

 The course is designed to provide comprehensive knowledge to the students regarding the effect of IPR especially of patents on emerging issues like public health, climate, and the ways to tackle this problem.

Course Objective:

1. To provide comprehensive knowledge to the students regarding the Entrepreneurship and general principles of IPR, Concepts and Theories,

2. To provide comprehensive knowledge to the students regarding Indian position of the Copyright Law, 1957, Historical background and Development of Copyright Law, Infringement.

3. To provide comprehensive knowledge to the students regarding Indian position of the Trademark Act, 1999, Historical development of the concept of trademark and trademark law.

Meaning and importance of Entrepreneurship, Factors influencing entrepreneurship, characteristics of entrepreneurship, types of entrepreneurship, objectives of entrepreneurship development, Startups- Definition, Types.

Entrepreneurship Development Skills: Types of entrepreneurial skills - team work and leadership skill, analytical and problem solving skills, critical thinking skills, branding, marketing and networking skills. 

Institutions supporting Entrepreneurs: Various Central and State Level Organizations which Help the Entrepreneurs, Banks and non banking financial organisations, Fund Collection for Entrepreneurship

Preparation of Business model/Plan: Business plan - concept, format, components of business plan. Significance of Business Plan. Making of a Business plan.

Need for intellectual property rights. Rationale for protection of IPR. Impact of IPR on development. health, agriculture. IPR in lndia.

Concepts of Novelty, Utility Inventiveness/Non-obviousness, Patentable subject matter, Patentability criteria, non-patentable inventions Pharmaceutical products and process and patent protection Software Patents Patenting of Micro-organism, Rights of patentee Procedure for granting a patent and obtaining patents Grounds for opposition Surrender, Revocation, restoration Transfer of patent rights, Infringement.

Copyright Act, 1957 Terms of Copyright conditions for grant of copyright, extent of rights exception to copyright protection, fair use provision, assignment and licensing, Copyright in Literary, Dramatic and Musical ,Works, Sound Recording, Cinematograph Films, Copyright in Computer Programme, Author Special Rights, Right of Broadcasting and performers.

Historical development of the concept of trademark and trademark law-National and International Introduction to Trademarks Need for Protection. Kinds of trademarks Concept of Well-known trademark. 

T2. P. Narayanan (Eastern Law House), Intellectual Property Law.

R2. R.K. Nagarjan, Intellectual Property LawGanguli (Tata Megraw), Intellectual Property Rights

R3. Anjan Raichaudhuri, Managing New Ventures Concepts and Cases, Prentice Hall International.

R4. S. R. Bhowmik & M. Bhowmik, Entrepreneurship, New Age International.

R5. Steven Fisher, Ja-nae’ Duane, The Startup Equation –A Visual Guidebook for Building Your Startup, Indian Edition, McGraw Hill Education India Pvt. Ltd.

R6. Byrd Megginson, Small Business Management An Entrepreneur’s Guidebook, 7th ed, McGrawHill

R7. A Fayolle Entrepreneurship and new value creation,Cambridge, Cambridge University Press.

R8.N.S. Gopalakrishnan & T.G. Agitha, Principles of Intellectual Property (2009), Eastern Book Company, Lucknow.

R9.W. Cornish (Universal Publication), Intellectual Property Law.

·        CIA 2 – 50 Marks

·        CIA 3 – 20 Marks

·        End Semester Examination – 50 Marks

·        Attendance – 5 Marks

(Scaled: CIA – 25 Marks & ESE – 25 Marks)

COURSE DESCRIPTION:

This course, Discrete Mathematics (MA334) is offered for three credits in the third semester for the branch of Computer Science Engineering and Information and Technology for different streams. This course develops the logical augmenting and it has topics like Propositional Calculus, Set theory, Group theory, and Coding various Counting techniques.

COURSE OBJECTIVE:

The objective of the paper is to apply logical reasoning to validate the computer algorithms, to perform the operations associated with sets, functions, relations and groups for the coding and decoding information to check the security of the data. 

Propositions – Logical connectives – Compound propositions – Conditional and bi conditional propositions – Truth tables – Tautologies and contradictions – Contrapositive – Logical equivalences and implications – De Morgan’s Laws - Normal forms, Rules of inference – Arguments - Validity of arguments.

Basic concepts of Sets - Subset – Algebra of sets – The power set – Ordered pairs and Cartesian product – Relations on sets –Types of relations and their properties – Matrix and Graph representation of a relation – Partial ordering – Poset – Hasse diagram – Lattices and their properties – Sublattices – Boolean algebra.

Properties – Subgroups - Cosets and Lagrange’s theorem – Normal subgroups – Algebraic system with two binary operations – Preliminaries of Coding -  Hamming Metric  - group codes: –  Basic notions of error correction - Error recovery in group codes.

Types of functions - Examples – Composition of functions – Inverse functions – Characteristic function of a set, Mathematical Induction, The Rules of Sum and Product, Permutations, Combinations.

Fundamental principles of counting, pigeonhole principle, principle of inclusion and exclusion, Solving Linear Recurrence Relations, Divide-and-Conquer Algorithms and Recurrence Relations, generating functions, Solve Recurrence Relations using Generating Functions.

T1. Trembly J.P and Manohar R, Discrete Mathematical Structures with Applications to Computer Science, Tata McGrawHill Pub.Co. Ltd, New Delhi, 2003. 

T2. Ralph. P. Grimaldi, Discrete and Combinatorial Mathematics: An Applied Introduction, Fifth Edition, Pearson Education Asia,Delhi, 2009.

1.      R1. Bernard Kolman, Robert C. Busby, Sharan Cutler Ross, Discrete Mathematical Structures,  Fourth Indian reprint, Pearson Education Pvt Ltd., New Delhi, 2003.

2.      R2. Kenneth H. Rosen, Discrete Mathematics and its Applications, Fifth Edition, Tata McGraw Hill Pub. Co. Ltd., New Delhi, 2003.

3.      R3. Richard Johnsonbaugh, Discrete Mathematics, Fifth Edition,Pearson Education Asia, New Delhi, 2002.

End Semester Examination(ESE)      : 50% (50 marks out of 100 marks) 

Components of the CIA

CIA I  :  Subject Assignments / Online Tests                  : 10 marks

CIA II :   Mid Semester Examination (Theory)                : 25 marks            

CIAIII: Quiz/Seminar/Innovative Assignments/presentations/publications : 10 marks

Attendance                                                                           : 05 marks

            Total                                                                                       : 50 marks

Mid Semester Examination (MSE) : Theory Papers:

• The MSE is conducted for 50 marks of 2 hours duration.
• Question paper pattern; Four questions have to be answered in part A without any choice. One question need to be answered out of two in part B. Each  question carries 10 marks

End Semester Examination (ESE):

The ESE is conducted for 100 marks of 3 hours duration.

The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

This course focuses on the fundamentals of psychology. It is an introductory paper that gives an overall understanding about the human behavior. It will provide students with an introduction to the key concepts, perspectives, theories, and sub-fields on various basic processes underlying human behavior.

Definition, Characteristics of Sensory modalities: Absolute and difference threshold; Signal detection theory; sensory coding; Vision, Audition, Other Senses. Assessment of Perception and Sensation

Practicum: Aesthesiometer

Definition, Understanding perception, Gestalt laws of organization, Illusions and Perceptual constancy; Various sensory modalities; Extrasensory perception.

Practicum:  Muller-Lyer Illusion

Learning:Definition, Classical conditioning, Instrumental conditioning, learning and cognition; Memory:  Types of Memory; Sensory memory, working memory, Long term memory, implicit memory, Constructive memory, improving memory; Assessment of memory.

Practicum: Memory drum

Concepts and nature of Individual differences; Nature vs. nurture; Gender difference in cognitive processes and social behavior; Intelligence: Definition, Contemporary theories of intelligence; Tests of intelligence; Emotional, Social and Spiritual intelligence.

Practicum: Bhatia’s Battery of Performance

Definition, Type and trait theories of personality, Type A, B & C. Psychoanalytic -  Freudian perspective; Types of personality assessment.

Rathus, S. A. (2017). Introductory Psychology, 5thEd. Belmont, CA: Wadsworth.

Nolen-Hoeksema, S., Fredrickson, B.L. & Loftus, G.R. (2014). Atkinson & Hilgard'sIntroduction to Psychology.16th Ed. United Kingdom: Cengage Learning.

Morgan, C. T., King, R. A., & Schopler, J. (2004). Introduction to Psychology. New Delhi: Tata     McGraw Hill.

Kalat, J. W. (2016). Understanding Psychology. New York: Cengage Learning.

This course is designed to provide a holistic development program combining personality enhancement, physical training, leadership skills, and technical expertise. Students will engage in physical training, learn fundamental drill techniques, and gain hands-on experience in aviation, including airmanship, aircraft forces, and specific technical details of the ZENAIR CH 701. The course also includes practical exercises such as obstacle courses and social service activities to foster leadership and community involvement. Through a blend of theoretical knowledge and practical skills, students will be well-prepared for roles requiring both personal development and technical proficiency.

Develop self-awareness, confidence, and leadership qualities through structured personality development and leadership training.

Understand the principles of airmanship and the forces acting on aircraft to enhance operational knowledge in aviation.

Engage in social service activities to build leadership skills and contribute positively to the community.

• Personality Development

  • Self-awareness and Confidence: Techniques to build self-esteem and self-awareness.
  • Effective Communication: Skills for clear and impactful communication.
  • Time Management and Goal Setting: Strategies to manage time efficiently and set achievable goals.

  • Fundamentals of Foot Drill

    • Basic Movements and Commands: Training in fundamental drill movements and commands.
    • Marching Techniques: Proper techniques for marching and maintaining formation.
    • Discipline and Synchronization: Importance of precision and coordination in drill routines.

• Airmanship

  • Principles of Airmanship: Understanding the essential principles for effective flight operations.
  • Safety Procedures: Best practices for ensuring safety in aviation settings.
  • Situational Awareness: Techniques to maintain awareness and make informed decisions during flight.

• Forces Acting on Aircraft

  • Aerodynamic Forces: Analysis of lift, weight, thrust, and drag.
  • Flight Performance: Impact of aerodynamic forces on aircraft performance.
  • Environmental Factors: Influence of environmental conditions on flight dynamics.

• Technical Details: ZENAIR CH 701

  • Aircraft Specifications: Overview of technical features and specifications of the ZENAIR CH 701.
  • Maintenance Procedures: Routine maintenance and inspection practices.
  • Performance Evaluation: Assessing the aircraft's performance characteristics and capabilities.

• Engine Performance

  • Diagnostic Techniques: Methods for diagnosing engine performance issues.
  • Maintenance Practices: Routine checks and maintenance to ensure optimal engine function.
  • Performance Analysis: Evaluating engine performance data and addressing operational issues.

• Obstacle Course

  • Course Navigation: Techniques for efficiently navigating and overcoming obstacles.
  • Agility and Coordination: Exercises to enhance physical agility and coordination.
  • Performance Evaluation: Assessing personal performance and identifying areas for improvement.

• Social Service Activity

  • Community Engagement: Planning and organizing activities that benefit the community.
  • Leadership and Teamwork: Applying leadership skills in social service projects.
  • Impact Assessment: Reflecting on the impact of social service activities on personal growth and community well-being.

2. Airwing Cadet Handbook, Common Subject SD/SW, Maxwell Press, 2015.

2. Airwing Cadet Handbook, Common Subject SD/SW, Maxwell Press, 2015.

Course Description:

This course covers technical reading and writing practices, professional communication for employment and at the workplace, and foundational mathematical concepts. It includes technical writing, report and proposal writing, listening and reading skills, job application preparation, group discussions, and presentation skills. It also addresses key mathematical topics such as number systems, percentages, data interpretation, ratios, speed, time, distance, and work-related problems. The course concludes with comprehensive training in C programming, covering data types, control flow, arrays, functions, structures, pointers, and file management.

Course Objective:

1. Develop Technical Reading Skills: Equip students with effective reading strategies for comprehending complex technical documents.

2. Enhance Technical Writing Abilities: Teach the processes involved in writing clear and concise technical reports and proposals.

3. Improve Grammar and Editing Skills: Strengthen students' understanding of grammar, voice, speech, and common errors in technical writing.

4. Professional Communication Mastery: Foster skills in professional communication, including job application processes, resume writing, and email etiquette.

5. Group and Interpersonal Communication: Cultivate effective group discussion, interview techniques, and interpersonal communication skills for professional settings.

1. Reading Process and Reading Strategies, Introduction to Technical writing process,
Understanding of writing process, Effective Technical Reading and Writing Practices , Introduction to
Technical Reports writing, Significance of Reports, Types of Reports.
2. Introduction to Technical Proposals Writing, Types of Technical Proposals, Characteristics of Technical
Proposals. Scientific Writing Process.
3. Grammar – Voice and Speech (Active and Passive Voices) and Reported Speech, Spotting Error Exercises,
Sentence Improvement Exercises, Cloze Test and Theme Detection Exercises.

Professional Communication for Employment :

1. The Listening Comprehension, Importance of Listening Comprehension, Types of Listening, Understanding

and Interpreting, Listening Barriers, Improving Listening Skills. Attributes of a good and poor listener.

2. Reading Skills and Reading Comprehension, Active and Passive Reading, Tips for effective reading.

3. Preparing for Job Application, Components of a Formal Letter, Formats and Types of official, employment,

Business Letters, Resume vs Bio Data, Profile, CV and others, Types of resume, Writing effective resume

for employment, Model Letter of Application (Cover Letter) with Resume, Emails, Blog Writing, Memos

(Types of Memos) and other recent communication types.

Professional Communication at Workplace :

1. Group Discussions – Importance, Characteristics, Strategies of a Group Discussions. Group

Discussions is a Tool for Selection. Employment/ Job Interviews - Importance, Characteristics,

Strategies of a Employment/ Job Interviews. Intra and Interpersonal Communication Skills -

Importance, Characteristics, Strategies of a Intra and Interpersonal Communication Skills. NonVerbal Communication Skills (Body Language) and its importance in GD and PI/JI/EI.

2. Presentation skills and Formal Presentations by Students - Importance, Characteristics,

Strategies of Presentation Skills. Dialogues in Various Situations (Activity based Practical

Sessions in class by Students)."                

· Divisibility & Remainder

 · Multiples & Factors

 · Integers

 · LCM & HCF.

 · Complete a number Series

 · Find the Missing Term and Wrong Term

 Simplification

 · BODMAS Rule

 · Approximation

 · Decimals

 · Fractions

 · Surds & Indices

Percentage

Calculation-oriented basic percentage, Profit and Loss, Successive Selling type, Discount & MP, Dishonest Dealings, Partnerships

Interest : Simple Interest, Compound Interest, Mixed Interest, Installments.

Data Interpretation: Approach to interpretation - simple arithmetic, rules for comparing fractions, Calculating (approximation) fractions, short cut ways to find the percentages, Classification of data– Tables, Bar graph, line graph, Cumulative bar graph, Pie graph, Combination of graphs. Combination of table and graphs

· Simple Ratios

 · Compound Ratios

 · Comprehend and Dividend

 · Direct & Indirect Proportions

 · Problems on ages

 · Mixtures & Allegation

Speed, Time and Distance

 · Relative Speed

 · Average Speed

 · Problems on Train

 · Boat & Stream.

 Time and Work

 · Work Efficiency

 · Work & Wages

 Pipes & Cisterns

Data Types, Operators and Expressions  Input and output Operations  Control Flow – Branching, Control Flow – Looping  · Statements and Blocks  · If..Else, Switch, Nesting of If..Else  · GOTO statement  · The while statement  · The For statement  · The Do statement  · Jumps in loops

Arrays, Strings

 · One-dimensional arrays

 · Initialization of one-dimensional arrays

 · Two-dimensional Arrays

 · Initializing Two-dimensional arrays

 · Multi-dimensional arrays

 · Dynamic arrays

 · Declaring and Initializing string variables

 · Reading Strings from Terminal

 · Writing Strings to screen

 · String handling functions

 · Operations on strings

User-defined Functions, Structures

 · Basics of Functions

 · Functions Returning Non-integers

 · External Variables, Scope Rules

 · Header Files, Static Variables, Register Variables

 · Block Structure, Initialization, Recursion

 · Category of functions, Functions that return multiple values

 · Nesting functions, Multi-file programs

 · Structures and Functions, Arrays of Structures

 · Pointers to Structures, Self-referential structures

Unions, Pointers

 · Difference between Structures and Unions

 · Accessing the address of a variable

 · Declaring and Initializing pointer variables

 · Accessing a variable through its pointers

 · Chain of pointers

 · Pointer Expressions

 · Pointer Increments and Scale Factors

 · Pointers and character strings

 · Array of pointers

 · Pointers as function arguments

 · Functions returning pointers

 · Pointers to functions, Drawback of Pointers

File Management in C, The Preprocessor

 Defining and Opening a File, Closing a File, Input / Output Operations on Files, Random Access to Files, Command Line Arguments. Macro Substitution, File Inclusion, Compiler Control Directives, ANSI Additions.

Author: Gopalaswamy Ramesh and Mahadevan Ramesh

Publisher: Pearson Education India

Edition: 1st Edition (2010).ISBN: 9788131732857.

2.Title: The ACE of Soft Skills: Attitude, Communication and Etiquette for Success

Author: Gopalaswamy Ramesh and Mahadevan Ramesh

Publisher: Pearson Education India

Edition: 1st Edition (2010)

ISBN: 9788131732857                                       

    Author: R.S. Aggarwal

    Publisher: S. Chand Publishing

    Edition: 2021

    ISBN: 9789352836509

2. Title: How to Prepare for Quantitative Aptitude for the CAT

    Author: Arun Sharma

    Publisher: McGraw Hill Education

    Edition: 10th Edition (2022)

    ISBN: 9789354720196

. Title: Quantitative Aptitude for Competitive Examinations

    Author: R.S. Aggarwal

    Publisher: S. Chand Publishing

    Edition: 2021

    ISBN: 9789352836509

3. Title: How to Prepare for Quantitative Aptitude for the CAT

    Author: Arun Sharma

    Publisher: McGraw Hill Education

    Edition: 10th Edition (2022)

    ISBN: 9789354720196.

Title: Let Us C

    Author: YashavantKanetkar

    Publisher: BPB Publications

    Edition: 17th Edition (2020)

    ISBN: 9789388511393

4. Title: Let Us C Solutions

    Author: YashavantKanetkar

    Publisher: BPB Publications

    Edition: 13th Edition (2021)

    ISBN: 9789387284588

5. Title: The C Programming Language

    Author: Brian W. Kernighan and Dennis M. Ritchie

    Publisher: Prentice Hall

    Edition: 2nd Edition (1988)

    ISBN: 9780131103627

Overall CIA=50.

This course comprehensively deals with interdisciplinary engineering and design processes to achieve sustainability in the area of renewable energy, resources and waste management through experiential learning

Project based on solar energy

Projects based on water and other resources

Projects based on waste management

2.Kerr, Julie. Introduction to energy and climate: Developing a sustainable environment. CRC Press, 2017.

Students would be assessed  after every engagement for submissions and progress achived with respect to project- 50 marks

Students projects at the end of semester  would be assessed for  50 marks by panel constituted by the department- 50 marks

Course Description:

 This course provides an overview of different types of operating systems. It helps to understand the components of an operating system including process management and storage management. It also covers the basic concepts of I/O and file systems.

Course Objective:

The main objectives of the course are:

1: To describe the necessity and importance of Operating Systems.

2. To clarify the process management principles for given problem using appropriate tools.

3: To make the students understand, process synchronization mechanisms, deadlock environment, and memory management strategies on file systems.

Introduction: What operating systems do?, Computer System computer , Operating System Structure, Operating System Operations, Process Management, Memory Management, Storage Management, Protection and Security; System Structures: Operating System Services, User Operating System Interface, System Calls, Types of System Calls.

Experiment 1:  Shell programming

a. command syntax (DATE, CAL, ECHO, CLEAR, WHO, CAT, PWD, MKDIR, CD, LS, RM, TR, HEAD, MORE , SORT, GREP, etc..)

b. write simple functions (Create a user defined function that include special

commands. Eg: list () { ls | less; })

c. basic tests (simple if-fi, if-else-fi, if-elif…fi, while, for, case-esac )

Experiment 2:  Shell programming

a. expansions (generate two or more commands from a single typed command.)

Eg: Mkdir college/jan

Mkdir college/feb

Mkdir college/Mar

Mkdir college

Mkdir college/{jan,feb,Mar}

b. substitutions:- insert the output of a command within a command

Command substitution is the mechanism by which the shell performs a given set of commands and then substitutes their output in the place of the commands. Syntax:- `command` Eg: USERS=`who | wc –l` Echo “Logged in user are $USERS

Process Management: Process Concept, Process Scheduling, Operations on Processes, Inter-process Communication; Threads: Overview, Multithreading Models, Thread Libraries; CPU Scheduling: Basic Concepts, Scheduling Criteria, Scheduling Algorithms, Multiple- Processor Scheduling

Experiment 3: Write programs using system calls( fork( ),exit( ),getpid( ), sleep( ) ) of UNIX operating system.

Experiment 4: Write programs using the I/O system calls ( opendir( ),closedir( ), readdir( ) )of UNIX operating system.

Process Synchronization: Background, The Critical Section Problem, Peterson’s Solution, Synchronization Hardware, Semaphores, Classical Problems of Synchronization, Monitors, Synchronization Examples, Deadlocks.

Experiment 5: Implement the following CPU scheduling algorithm compute average waiting time and average turnaround time. 

a.       FCFS 

b.     Round Robin 

c.     Shortest Job First 

d.      Priority

Experiment 6: Implement the Inter Process Communication. (Creation of Shared memory Segment/Semaphores).

Memory Management: Background, Swapping, Contiguous Memory Allocation, Paging. Virtual Memory : Background, Demand Paging, Copy on Write, Page Replacement, Allocation of frames, Thrashing, Allocating Kernel Memory.

Experiment 7: Implement Bankers Algorithm

Experiment 8: Implement some memory management schemes -I

File System Interface: File System: File Concept, Access Methods, Directory Structure, File System Mounting, File Sharing, Protection. File System Implementation & Mass Storage Structure: Implementing File Systems: File System Structure, File System Implementation, Directory Implementation, Allocation Methods, Free Space Management. Disk structure, Disk Attachment, Disk Scheduling Methods, Disk Management, Swap-Space Management.

Experiment 9: Implement some memory management schemes – II.

T2. Harvey M. Deitel, “Operating Systems”, Pearson Education Pvt. Ltd, Third Edition, 2008.

R2. William Stallings, “Operating System- Internals and Design Principles”, Pearson Education, Nineth Edition, 2018.

R3. Pramod Chandra P. Bhatt – “An Introduction to Operating Systems, Concepts and Practice”, PHI, Fifth Edition, 2019.

•       CIA 1 – 20 Marks

•       CIA 2 – 50 Marks

•       CIA 3 – 20 Marks

•       Practical – 50 Marks

•       End Semester Examination – 100 Marks

•       Attendance – 5 Marks

(Scaled: CIA (Theory + Practical) –  70  Marks & ESE – 30 Marks)

Course Description:

 The objective of the course is to present an introduction to database management systems, with an emphasis on how to organize, maintain and retrieve - efficiently, and effectively - information from a DBMS. This course addresses the local application needs. The course helps in skill development and employability. 

Course Objective:

1. To learn the fundamentals of data models and to conceptualize and depict a database system using ER diagram. 
2. To make a study of SQL and relational database design. 
3. To have an introductory knowledge about the emerging trends in the area of distributed DB and implement the design of the tables in DBMS. To write queries to get optimized outputs
4. To understand the internal storage structures using different file and indexing techniques which will help in physical DB design. 
5. To know the fundamental concepts of transaction processing- concurrency control techniques and recovery procedure.

Introduction to File and Database systems- Database system structure – Data Models – Introduction to Network and Hierarchical Models – ER model – Relational Model – Relational Algebra.

Experiment 1: Database design using E-R model and its components.

SQL – Data definition- Queries in SQL- Updates- Views – Integrity and Security – Relational Database design – Functional dependencies and Normalization for Relational Databases (up to BCNF).

Experiment 2:  DDL, DML, and DCL commands in RDBMS

Experiment 3: Normalization and Implementation of Joins and Views

Experiment 4: High-level language extension with Cursors and Triggers

Introduction to NOSQL Systems, The CAP Theorem, Document-Based NOSQL Systems and MongoDB, NOSQL Key-Value Stores, Column-Based or Wide Column NOSQL Systems, NOSQL Graph Databases and Neo4j

Experiment 5: No Sql using monogoDB 

Record storage and Primary file organization- Secondary storage Devices- Operations on Files-Heap File- Sorted Files- Hashing Techniques – Index Structure for files –Different types of Indexes- B-Tree – B+ Tree – Query Processing.

Record storage and Primary file organization- Secondary storage Devices- Operations on Files-Heap File- Sorted Files- Hashing Techniques – Index Structure for files –Different types of Indexes- B-Tree – B+ Tree – Query Processing.

Experiment 6: Mini Project

http://db-book.com/db6/slide-dir

•       CIA 1 – 20 Marks

•       CIA 2 – 50 Marks

•       CIA 3 – 20 Marks

•       Practical – 50 Marks

•       End Semester Examination – 100 Marks

•       Attendance – 5 Marks

(Scaled: CIA (Theory + Practical) –  70  Marks & ESE – 30 Marks)

Course Description:

This course describes an overview of the concepts in Computer Networks and the functionality of Protocols used in OSI and TCP/IP layered architecture. The course will focus on the design, implementation, analysis, and evaluation of large-scale networked systems. The structure of this course is designed specifically for the students to understand the fundamentals of networks theoretically and to acquire practical Hands-on skills on working with various protocols and networking devices in the TCP/IP Model. This course describes an overview on the future modern networking technologies and the requirements that have evolved for the future networking environment. At the end of the course, the students find themselves comfortable in taking either of the direction- industrial job or further research in networking.

Course Objective:

The objective of the course is to understand

1. Basic functionality of OSI and TCP/IP architecture

2. Protocol functionality of TCP/IP Model

3. Analysis of different MAC, IP, Routing, Transport, and application layer protocols.

4. Requirements for the future Internet and its impact on the computer network architecture

Introduction- Data communications: Components - Data Communication- Data Flow- Network Topologies Categories of Network – Protocol Layering –OSI Model-TCP/IP Protocol Suite. Digital Transmission – Digital to Digital Conversion- Line coding -Line Coding Schemes –Introduction to Transmission Media.

Experiment 1: Study of various Networking Tools

Experiment 2: Simulating a Local Area Network

Introduction – Link Layer Addressing – Error Detection and Correction- Cyclic Codes- Check sum- Forward Error correction –Data Link Layer Protocols- Automatic Repeat (ARQ) protocols -Stop and Wait, Go-Back-N, Selective Repeat, HDLC.

Experiment 3: Implementation of stop and wait

Experiment 4: Implementation of CRC method for Error detection.

Introduction – Network-Layer Services– Packet Switching– IPv4 Addresses – Internet Protocol (IP)-IPV4, IPv6, Subnetting. Introduction - Routing Algorithms- Distance Vector Routing, Link State Routing, Path Vector Routing, Unicast Routing Protocols- RIP, OSPF.

Experiment 5: Implementation of RIP routing Protocol

Experiment 6: Implementation of OSPF routing Protocol

Introduction – Services, Port Numbers, User Datagram Protocol- User Datagram, UDP Services, UDP Applications. Transmission Control Protocol- TCP Services, TCP features. Congestion control - Flow Control to Improve Qos

Experiment 7: Socket Programming: Implementation of UDP protocol client server Communication

Experiment 8: Socket Programming: Implementation of TCP Protocol for client server Communication

Introduction – DNS- SMTP- DHCP- FTP- HTTP-Telnet. Network Security-Introduction-Security Goals- Attacks- Firewalls. Foundations of Modern Networking-Introduction: Software Defined Networking -SDN Architecture, Virtualization.

Experiment 9: Implementation of SMTP and FTP protocol.

Experiment 10. Implementation of DHCP protocol.

R2. Larry L. Peterson, Bruce S. Davie, Computer Networks (2021): A Systems Approach (The Morgan Kaufmann Series in Networking), Morgan Kaufmann. ISBN- 9780128182000

•       CIA 1 – 20 Marks

•       CIA 2 – 50 Marks

•       CIA 3 – 20 Marks

•       Practical – 50 Marks

•       End Semester Examination – 100 Marks

•       Attendance – 5 Marks

(Scaled: CIA (Theory + Practical) –  70  Marks & ESE – 30 Marks)

Course Description:  

The Python programming language is introduced in this course.  Basic programming ideas including variables, functions, loops, conditionals, and data structures are taught to the students.  Students who complete this course receive an understanding of the numerous tools available for writing and running Python Codes.  In addition, it offers practical coding assignments that involve creating custom functions, reading and writing to files, and utilizing widely used data structures.

Course Objectives:

1.     To understand the fundamentals of Python Programming.

2.   To apply Python Programming Constructs for solving real life problems in the domain of engineering, business, health care, and other social applications.

Installing a complete Python environment, Python Introduction, Keywords and Identifiers, Statements and comments, Python Data types, Python I/O and import, Python Operators, Basic Mathematics, Variables, Strings and text, Interacting with users. Illustrative Programs using Variables and Data Types: Numeric, Lists, Strings, tuples, Sets, and Dictionary; Illustrative Programs using Operators:  Arithmetic, Comparison, Assignment, Logical, Bitwise, Membership, and Identity.

List of Experiments:

1.     Print “Hello World”

2.     Simple Mathematical Calculator

3.     Area of Triangle

4.     Find Square Root

5.     Swap the contents of two Variables

6.     Generate Random Number

7.     Convert Kilo meters to Meters

8.     Convert Celsius to Fahrenheit

9.     Calculate Salary of an Employee

10.   Find Simple Interest

11.   To accept the marks of 3 subjects and hence find the percentage scored

12.   Simple Exercises on Lists, Strings, Sets and Dictionary

Looping and logic, Python Flow Control, if-else, for loop, while loop, break and continue, Illustrative programs, Python Functions, Python Functions, function argument, python recursion, python module, python package. Illustrative Programs using Conditional Statements:  If, Elif and Else; Loops:  While, for and nested loops; Functions

List of Experiments:

1.     Check whether a given number of Odd or Even

2.     Smallest of three Numbers

3.     Whether a given Number is Positive, Negative or Zero.

4.     Solve Quadratic Equation

5.     Prime Number or not

6.     Print all Prime Numbers in an Interval

7.     Factorial of a Number

8.     Fibonacci Series

9.     Sum of Natural Numbers

10.   Convert Decimal to Binary, Octal and Hexadecimal

11.   GCD and LCM

12.   Find the Factors of a Number

13.   Matrix Multiplication using Functions

14.   Transpose of a Matrix using Functions

15.   Remove Punctuations from a String

16.   Concatenate two Strings using Functions

17.   nCr using Recursion (Binomial Coefficient)

18.   Decimal to Binary Conversion using Recursion

Data structures using lists, Tuple and dictionaries; Lists: list operations, list slices, list methods, list loop, mutability, Tuples; Dictionaries: operations and methods.

List of Experiments:

1.     Sort a List using Functions

2.     Merge two Lists using Functions

3.     Addition and Multiplication of the Lists

4.     Sum all the items in a List.

5.     Get the largest number from a List.

6.     Remove duplicates from a List.

7.     Append a List to the second List.

8.     Insert an element at a specified position into a given List.

9.     Check whether an element exists within a Tuple. 

10.   Reverse a Tuple.

11.   Sort (ascending / descending) a Dictionary by value.

12.   Sort a given Dictionary by key. 

13.   Concatenate following dictionaries to create a new one. 

Sample Dictionary:
dic1 = {1:10, 2:20}
dic2 = {3:30, 4:40}
dic3 = {5:50,6:60}
Expected Result: {1: 10, 2: 20, 3: 30, 4: 40, 5: 50, 6: 60}

Files: text files, reading and writing files, format operator; modules, packages; Illustrative programs: word count, copy.

List of Experiments:

1.     Read a File Line by Line into a List

2.     Append to a File

3.     Extract Extension from a File Name

4.     Copy a File

5.     Find Hash of a File

6.     Get the File Name from the File Path

7.     Count number of Lines in a File

8.     Word Count in a File

9.     Count uppercase character in a text file

Python Basics for Data Analysis and Visualization: Loading, Cleaning and Exploring and Visualization. Python Libraries (NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn), Machine Learning and its Use Cases.

Experiments Details:

A Real Time Project Implementation which involves the following:

·       Reading a Real Time Data Set

·       Exploratory Data Analysis

·       Data Visualization

·       Data Preprocessing

·       Any two Machine Learning Models and its Analysis

T2: Guido van Rossum and Fred L. Drake Jr, “An Introduction to Python – Revised and updated for Python 3.2, Network Theory Ltd., 2011. (reprint)

R2:  John V Guttag, “Introduction to Computation and Programming Using Python’’, Revised and expanded Edition, MIT Press, 2013 (reprint)

R3: Kenneth A. Lambert, “Fundamentals of Python: First Programs”, CENGAGE Learning, 2012.

R4: Paul Gries, Jennifer Campbell and Jason Montojo, “Practical Programming: An Introduction to Computer Science using Python 3”, Second edition, Pragmatic Programmers, LLC,2013.

R5: Robert Sedgewick, Kevin Wayne, Robert Dondero, “Introduction to Programming in Python: An Interdisciplinary Approach, Pearson India Education Services Pvt. Ltd., 2016.

R6: Timothy A. Budd, “Exploring Python”, Mc-Graw Hill Education (India) Private Ltd., 2015.

•       CIA 1 – 20 Marks

•       CIA 2 – 50 Marks

•       CIA 3 – 20 Marks

•       End Semester Examination – 50 Marks

•       Attendance – 5 Marks

(Scaled: CIA – 25 Marks & ESE – 25 Marks)

Course Description:

This course provides a strong foundation of fundamental concepts in Artificial Intelligence. It aims to provide a basic exposition to the goals and methods and to enable the student to apply these techniques in applications which involve perception, reasoning and learning.

Course Objective:

1. To gain knowledge in the basics of Artificial Intelligence.

2. To analyze the applicability of searching algorithms in real time scenarios.

3. To acquire knowledge on knowledge representation and Learning.