MCA Course Syllabus 2024: Subjects, Semester-wise Syllabus PDF, Top Colleges, Books

Subject title

Subject Details 

Mathematical Foundations of

Computer Science

Statement (Proposition), Logical Connectives, Conditional, Bi-conditional, Converse, Inverse, Contrapositive, Exclusive

OR, NAND, NOR, Tautology, Contradiction, Satisfiable, Duality Law, Algebra of propositions, Mathematical Induction; Set Theory, Combinatorics and Discrete Probability

Database Management System

Database System Applications, View of data, Advantages, Database languages, users and Administrator, Architecture, SQL, Data Definition,

Basic operations, Basic structure of SQL queries, Set operations, Aggregate Functions, Null values

Object Oriented Programming

Elements of Object Oriented Programming: Object, Encapsulation & data abstraction, Classes, Inheritance and Polymorphism. Programming Basics, Type conversion, Loops and Decision, Structures,

Enumerated Data Types, Simple functions

Operating Systems

Simple, multiprogrammed batch systems, distributed systems, time-sharing & real time systems, Algorithms thrashing Deadlocks, Concurrent Process

Software Engineering

Software Product, Development approaches and team structures, Process models and SRS: Various Process models, Requirements Functional and

non-Functional, Software Document, Requirement Engineering Process, Feasibility Studies, Software Prototyping, Functional models, Structured

Analysis, Design Concepts and Principles

Java Programming

Java Development Kit, Java RunTime Environment, Java Virtual Machine, Bytecode. Java data types, keywords, operators, Type conversion, Arrays, Ragged arrays, ArrayLists

Data Structures and Algorithms

Basic Concepts: Pseudocode, The Abstract Data Type, Model for an Abstract Data Type, ADT Implementation, Algorithm Efficiency, Time and Space Complexities, Asymptotic Notations, Recursion, Queues, Trees, Graphs

Web Technologies

Introduction to HTML, Structure of HTML Document, Semantics of HTML Elements and Attributes, HTML Tables and Forms, Introduction to CSS, Types of Styles, Selectors, Style Cascade, The Box Model, Text Styling, PHP Controls, PHP Functions, PHP Arrays.

Data Analytics

Data science, steps in data analysis projects,  need for analytics, Data- sources of data, data warehouses, data sets, data types, privacy & confidentiality,  transformation, samples vs. population,dimensionality reduction, Data Analysis and Visualisation

Machine Learning

Introduction, Applications, Probability, Parametric Classification, Regression, Tuning Model Complexity, Clustering, regression

Computer Networks

need for layered architecture and comparison between ISO/OSI, TCP/IP layered models. Significance of

Data Link layer and protocols. Network layer functionalities, classless IP addressing, classful, address allocation and role of forwarding module in

forwarding the packet using the routing table.

Subject Title

Subject Details 

Microprocessors

Inductive learning, Learning Concepts and rules from Examples, Learning by analogy, Learning from observation and discovery, Learning by experimentation, Learning by training Neural Networks; Genetic Based Machine Learning (GBML) Learning Classifier Systems (LCS), Genetic Programming.; Analytical learning

Advanced Data Structure and Algorithms

Review of basic data structures, Dynamic data structures, Approximation

Algorithms,  Analysis of the expected time complexity of the algorithms. Probabilistic Algorithms & Randomised

Algorithms.

Advanced Computer Architecture

Register Transfer and Micro operations:. Register Transfer language, Register transfer, Bus and Memory Transfer, Arithmetic Micro operations, Logic Micro operations, Shift Micro operations and Arithmetic logic shift units, computer arithmetic

Web Based Programming

Word Wide Web – introduction, Web servers, Client-Server model, Browser

architecture, Browser Interface,

optional clients, Search engines, optimization of search engines, caching in web browser, CGI

interface; Scripting languages – JSP, ASP; Hypertext – HTML, DHTML, HTTP; Web Programming- Java

language, Java Beans, Java Swings, Java utilities, Servlets, Applets, RMI.

Cloud Computing and IoT

Cloud Computing Fundamentals, Cloud services: Benefits and challenges of cloud

Computing, Types of cloud, Key

Characteristics of Cloud Models, Grid Computing, Cluster Computing, Grid Computing v/s Cloud Computing

Compiler Design

Overview of a Compiler, Lexical Analyzer, Syntax Analysis: PDA, NPDA, Construction of Top-down and Bottom-up parsers from CFG, Recursive descent parser, Operator precedence parser, LR parsers, Semantic Analysis, code optimisation

Wireless Networks

Introduction to Wireless Networks, Wireless Transmission, Modulation techniques - analog modulation and digital modulation, Spread Spectrum technology, Wireless Medium Access Control, Mobility and Mobile IP, TCP Over wireless

Networks, Mobile Ad Hoc Networks.

Parallel and Distributed Systems

Parallel systems, hardware, SIMD, MISD, MIMD, Multiprocessor systems, Parallel algorithms, Shared memory, message passing, and data parallel programming, Shared memory multiprocessors, Synchronisation, Distributed object-based systems, Distributed file systems.

Semester

Core/Elective

Subject title

Subject Details 

First

Core

Core

Core

Core

Core

Core

Programming in C

Computer Fundamentals

Data Structures

Discrete Mathematics

Computer Architecture

Numerical Methods

Program design and analysis using the C programming language, basic data types and their operators, control structures, arrays,

string, structs and unions, dynamic memory allocation, pointers and pointer arithmetic,

and files.

Logic gates, Boolean algebra, K-map, Map simplification, Combinational circuit Design, Sequential Circuit Design, Logic Design, Processor Control Logic Design, Digital Integrated circuits

Classification of Data Structures,  Tree and tree operations,  Shortest path algorithm, Fundamentals of the Analysis of Algorithm Efficiency, Recursion

Sets, Functions, Relations, Logic operators, normal forms, truth tables, Propositional and predicate

calculus, Euclidean algorithms, Boolean Algebra, Fibonacci numbers

Data representation – two’s complement, number system, Arithmetic operations using 2’s and 1’s

complements, floating-point representation and arithmetic operations; Input output organisation –I/O verses memory

bus, Isolated versus memory mapped I/O, Priority interrupts, DMA, I/O processors; Memory Organisation–

RAM, ROM, Associative memory, Cache memory

Data representation – Fixed-point numbers, Finite data representation;Floating-point numbers,

Propagation of error, Root finding’ Newton’s methods,

Gaussian

numerical integration, Solution of systems of linear equations – matrix equation, method of triangular

matrics, Gaussian elimination with pivoting, Jacobson and Gauss Seidel; Ordinary Differential equations –

Euler method, Multi-step method, Runga-Kutta methods, System of differential equations.

Second

Core

Core

Core

Core

Core

Core

Database Management Systems

Computer Networks

Design and Analysis of Algorithms

Object Oriented Programming

Artificial Intelligence

Operating Systems

Database Architecture, Database Analysis, Database Design,

Normalisation, Lossless Join Decomposition and Relational Algebra, Tuple and Domain Relational

Calculus, Concurrency Control and Recovery

Techniques, Advances in Database Systems and Technologies

Overview of Computer Network, Data Communication, , Nyquist theorem, Shannon’s formula, modulations, encoding schemes, ALOHA systems, Local Area Networks, Token Ring, Token Bus, FDDI, Routing, congestion

control, Application Protocols – FTP, Email.

Some efficient algorithms; Algorithm analysis: worst case and average case analysis, Recurrences and

asymptotics; Algorithm design, Efficient data structures, amortised analysis, NP completeness

The Key Attributes of Object-Oriented Programming, The Java Class Libraries, The Java Development Kit.

Java’s Primitive Types, The Scope and Lifetime of Variables, Literals, Shorthand Assignments, operators,

Type conversion in Assignments, Using Cast. Control Statements, Recursion, Inheritance Basics, Member Access and Inheritance

Overview of AI, Problem solving, various search strategies,

Introduction to logic programming, Knowledge representation, Conceptual dependency, Uncertain knowledge and reasoning, Hill Climbing, Simulated

Annealing, Best First Search.

Overview, Operating System Structures, Computer System Structures, Process and Process Scheduling,

CPU scheduling, Process Synchronisation, Paging, Segmentation, Virtual Memory, File System Allocation methods, Secondary Storage Scheduling and

Management, Protection, Security

Third

Core

Core

Elective

Elective

Elective

Elective

Software Engineering

Theoretical Computer Science

Microprocessors

Computer Graphics and Multimedia

Probability and Statistics

Machine Learning

Introduction, Software Process Models, Software Product and Process, Engineering,

Requirements

Requirements Analysis –Data Flow Diagram, Requirement Specification, Requirement Validation;

Design- Concepts, Cohesion, Coupling, User Interface Design, Mapping Analysis to Design, Structure

Charts, CASE Tools, Software Maintenance and

Reengineering.

Mathematical reasoning; logic; methods of proof; sets, relations, function, Kleen’s theorem, Moore and

Mealy models; Turing machine; Pushdown automata; Recursive and recursively enumerable sets models,

recursive functions.

Basic Microprocessor architecture, memory systems for microprocessor, bus structure and memory maps,

hardware and software interrupts, I/O systems Introduction to Intel family of microprocessor, 8085/8086

microprocessor - architecture, Instruction set, programming.

Graphics devices – random scan and Raster-scan; Bresenahm’s circle drawing algorithm, generation of ellipses, 2-D graphics: polar coordinates, parametric

functions, vectors, matrices operations; 3-D graphics:

transformation- right handed coordinate system with vertical y-axis, matrices for translation, scaling

rotation around axis

Probability – Conditional probability, Axioms, Bayes Theorem, Discrete RV – Binomial, random variables,

geometric Poisson,  Continuous RV, Hypothesis testing, Curve fitting, Methods of least Squares, Curvilinear

Multiple regression.

An overview of Machine learning; Inductive learning, ID3, C4.5; Learning Concepts and rules from

Examples; Learning by analogy; Learning from observation and discovery; Learning by experimentation.

Fourth

Core

Project

Students have to complete a project by designing a computer application using the knowledge gained during the previous three semesters.

Specialisation

Specialisation Subjects

Specialisation Details

Data Mining

Data Processing

Mining Frequent Patterns And Advanced Pattern Mining

Classification Techniques

Clustering Techniques

Outlier Detection and Application

Students learn to process and analyse data, create models and algorithms and use data mining techniques.

Internet of Things

IoT Introduction

IoT Programming

IoT Applications

Network of Wireless Sensor Nodes

MAC, Routing, and Transport Control in WSN

This includes IoT physical design, communication models and IoT enabled technologies to create applications.

Artificial Intelligence

Introduction to Artificial Intelligence

Local Search Algorithms

Knowledge Representation

Game Playing

Natural Language Processing

Review and analysis of complex systems by developing an understanding of the issues involved in defining and simulating perception, comparing and contrasting different AI techniques.

Wireless And Mobile Networks

Wireless Telecommunications Systems and Networks

Common Cellular System Components

Wireless Network Architecture and Operation

GSM and TDMA Technology

CDMA Technology, CDPD and Edge Data Networks

Wireless LAN/ PAN

Formation of basic wireless systems, their functioning, network architecture, data communication, and the functioning of mobile hardware.

Data Science

Data, Relations and preprocessing

Correlation and Regression

Association Rule Mining and Classification

Clustering and Time Series Analysis

Visualisation and Applications

Developing analytical skills to carry out research, improve businesses, work with large amounts of data, find relevant information and market trends from the data.

Digital Marketing

Going Digital - The Evolution Of Marketing

The Search For Success

Search Engine Optimization

Email Marketing And Social Media Marketing

Web Analytics

Develop a structured digital marketing plan and select strategic choices for increasing client acquisition, conversion, and retention. To make digital technology more accessible as a tool and possible requirement for competitive advantage.

Subject

Book Title

Authors

Computational Mathematics

Discrete Mathematics with Applications

Fundamental Approach to Discrete Mathematics

Thomas Koshy

D.P. Acharjya, Sreekumar

Database Management System

Database System Concepts

Database Management System

Abraham Silberschatz, Henry Korth, S. Sudarshan

Raghu Ramakrishnan, Johannes Gehrke

Object Oriented Programming

The Complete Reference C++

Object Oriented Programming in C++

Herbert Schildt

Robert Lafore

Operating Systems

Operating Systems Concepts

An Introduction to Operating Systems

A Silberschartz, Peter B. Galvin and Greg Gagne

H. M. Deitel

Software Engineering

Software Engineering

Software Engineering Concepts

Software Project Management in Practice

Ian Sommerville

Richard Fairley

Pankaj Jalote

Java Programming

Java The Complete Reference

Core Java: Volume I - Fundamentals

Herbert Schildt

Cay S. Horstmann

Data Structures and Algorithms

Data Structures – A Pseudocode Approach with C

Design and Analysis of Algorithms

Richard F. Gilberg and Behrouz A. Forouzan

S. Sridhar

Web Technologies

Fundamentals of Web Development

PHP and MySQL Web Development

Randy Connolly, Ricardo Hoar

Luke Welling, Laura Thomson

Data Analytics

Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining

Data Mining for Business Intelligence

Glenn J. Myatt, Wayne P. Johnson

Galit Shmueli, Nitin R. Patel, and Peter C. Bruce

Machine Learning

Introduction to Machine Learning

Machine Learning: A Probabilistic Perspective

Pattern Recognition and Machine Learning

Ethem Alpaydin

Kevin P. Murphy

Christopher M. Bishop

Computer Networks

TCP/IP Protocol Suite

Computer Networks

Behrouz A. Forouzan

Tannenbaum, A.S.

Internet of Things

Internet of Things – A hands-on approach

Architecting the Internet of Things

Arshdeep Bahga, Vijay Madisetti

Dieter Uckelmann, Mark Harrison, Michahelles, Florian

College/University/Institution

Syllabus PDFs

NIT Trichy

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Jawaharlal Nehru University

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University of Hyderabad

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Christ University, Bangalore

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Delhi University

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Banaras Hindu University

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VIT Vellore

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Fergusson College

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NIT Jamshedpur

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NIT Warangal

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