Syllabus for
Master of Computer Applications
Academic Year  (2022)

Department of Computer Science of CHRIST (Deemed to be University) strives to shape outstanding computer professionals with ethical and human values to reshape nation’s destiny. The training imparted aims to prepare young minds for the challenging opportunities in the IT industry with a global awareness rooted in the Indian soil, nourished and supported by experts in the field. 

VISION

The Department of Computational Sciences endeavours to imbibe the vision of the University “Excellence and Service”. The department is committed to this philosophy which pervades every aspect and functioning of the department.

MISSION

“To develop a computational scientist with ethical and human values”. To accomplish our mission, the department encourages students to apply their acquired knowledge and skills towards professional achievements in their career. The department also moulds the students to be socially responsible and ethically sound.

Master of Computer Applications is a Two year post graduate programme spread over six Trimesters. This programme strives to shape the students into outstanding computer professionals for the challenging opportunities in IT industry. It enables students to evolve from the stereo type thinking to better achievers and prepares them to scale the global standards. Curriculum incorporates the state of the art areas of IT industry to provide opportunity for extended study in an area of specialization. Programme Objective

Programme Outcome/Programme Learning Goals/Programme Learning Outcome:

PO2: Problem Analysis: Identify, formulate, research literature, and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines.

PO3: Design/Development of Solutions: Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.

PO4: Conduct Investigations of complex computing problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

PO5: Modern Tool usage: Create, select, adapt and apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations.

PO6: Professional Ethics: Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practices.

PO7: Life-long learning: Recognise the need, and have the ability, to engage in independent learning for continual development as a computing professional.

PO8: Project management and finance: Demonstrate knowledge and understanding of the computing and management principles and apply these to one?s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

PO9: Communication Efficacy: Communicate effectively with the computing community, and with society at large, about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.

PO10: Societal and Environmental Concern: Understand and assess societal, environmental, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practices.

PO11: Individual and Team Work: Function effectively as an individual and as a member or leader in diverse teams and in multidisciplinary environments.

The Department of Computational Sciences at CHRIST (Deemed to be University) Delhi- NCR has created a niche in the realm of higher education in India through its programmes. Currently, the Department offers a wide array of undergraduate courses with multiple specializations in the disciplines of Computer Science, Statistics & Mathematics. A dedicated research block with all the latest research facilities boosts the morale of the faculty and research scholars alike. This is an ideal place for students with a research blend of mind to explore his/her passion. Apart from academics, students are moulded holistically through various co-curricular and extracurricular activities.

To promote the holistic development of the students and to sustain the academic creativity and inventiveness of the faculty the department engages in numerous workshops, seminars, industrial interfaces, faculty development programmes and many such endeavours. It is equipped with a highly committed team of instructors having versatile experience in teaching and research. The department also provides opportunities to work on collaborative projects with industry and international universities.

To enable the students to learn the basic functions, principles and fundamental aspects of digital  design in terms of digital logic elements and circuits. To provide deep knowledge in designing and  analyzing combinational and sequential circuits. The course prepares students to perform the  analysis and design of various types of data storage and data transfer circuits.

Number system representation: Decimal number system- Binary number system- octal number  system- hexadecimal number system- number system representation- number system conversion signed number representation- complement system: 1’s complement – 2’s complement- 9’s  complement – 10’s complement- Binary arithmetic operations: addition- subtraction multiplication- division- Coding schemes: BCD, Gray code and ASCII code.

Introduction - Boolean Logics and Logic Gates -Universal Gates and properties- Boolean Algebra  Theorems - Boolean Function - Minterms- Maxterms- Karnaugh Map (K-Map)- Sum of Products  (SOP) and Product of Sums (POS). Don’t Care Conditions. 

Introduction- Combinational logic- Half Adder – Full adder- Half subtractor-Binary adder -Binary  adder subtractor- BCD adder- Binary multiplier- Encoder- Decoder- Multiplexer- Demultiplexer BCD to seven segment display 

Self-learning: Full subtractor and realization of adder, subtractor and multiplier using NAND  gates.

Sequential logic- Introduction-Latches- Clock - Types of Clock – positive, Negative edge triggered  - Flip-Flops (with Timing Diagram) - SR Flip Flop – D Flip Flop – JK Flip Flop -Edge Triggered  Flip Flops- Master-Slave JK Flip-Flop-Timing diagram. 

Introduction to Register and Counter – Shift registers – Serial Transfer – Modes of operations Serial in Serial Out (SISO) -Serial in Parallel out (SIPO) – Parallel in Serial Out (PISO)- Parallel in  Parallel out (PIPO)- Bidirectional Shift Register -Synchronous Counter - Asynchronous Counters - Binary Counters - Up/Down counter -BCD counter. 

Self -learning: Shift register with Parallel Load 

[1] Donald P Leach, Albert Paul Malvino, Goutam Saha, Digital Principles and Applications, 8th  Edition, Tata Mc Graw-Hill, 2018 

[2] Bartee, Thomas C, Digital Computer Fundamentals, Tata Mc Graw-Hill, 6th edition, 2016.

[3] William Stallings, Computer Architecture and Organization, PHI, 8th Edition, 2016.

[4] David A. Patterson and John L.Hennessey, Computer Organization and Design, Morgan  Kauffman / Elsevier, 5th edition, 2016. 

[5] Ata Elahi ,Computer Systems Digital Design, Fundamentals of Computer Architecture and  Assembly Language, Springer International Publishing, 2017 

50 % ESE

The main aim of this course is to provide the grounding knowledge of statistical methods for data analytics. Data summarization, probability, random variables with properties and distribution functions were included. Sampling distributions and their applications in hypothesis testing advanced statistical methods like ANOVA and correlation and regression analysis were included.

Definition of Statistics, applications, data types and measurements, graphical representation of data using histogram, line diagram, bar diagram, time series plots; measures of central tendency and dispersion; coefficient of skewness and kurtosis and their practical importance.

Random experiment, sample space and events. Definitions of probability, addition and multiplication rules of probability, conditional probability and some numerical examples; Random variables: Definition, types of random variables, pmf and pdf of random variables; Mathematical expectation: mean, variance, covariance, mgf and cgf of a random variable(s); Probability distributions: Binomial, Poisson and Normal distributions with their important characteristics.

Concepts of population, sample, parameter, statistic, and sampling distribution of a statistics; Sampling distribution of standard statistics like, sample mean, variance, proportions etc. t, F and Chi- square distributions with statistical properties.

Statistical hypotheses-Simple and composite, Statistical tests, Critical region, Type I and Type II errors, Testing of hypothesis – null and alternative hypothesis, level of significance, Test of significance using t, F and Chi-Square distributions (large sample case). Concept of interval estimation and confidence interval construction for standard population parameters like, mean, variance, difference of means, proportions (only large sample case).

[2] Douglas C Montgomery, George C Runger, Applied Statistics and Probability for Engineers, Wiley student edition, 2004.

[2] Levine, David M; Berenson, L Mark; Stephen, David, Statistics for Managers Using Microsoft Excel, 2nd Edition, PHI, New Delhi, 2012.

ESE: 50%

To acquire the fundamental knowledge of the operating system architecture and components.

Operating system definition, Computer system organization, structure, architecture and operations, process and storage management, Protection and security, Distributed systems, Special purpose systems, Linux Operating Systems. System structure: operating system services, user interface, system calls, system programs, OS design, Implementation and structure. 

Process concepts, scheduling, operations on processes, Inter process communication, Examples of IPC systems, Communication in client server systems, Threads, Multi threading models, threading issues, Basic concepts, scheduling criteria, scheduling algorithms

Critical section problems, Peterson solution, Introduction to semaphores, classic problems of synchronization, Monitors, System model, deadlock characterization, methods for handling deadlock, deadlock prevention, avoidance, detection and recovery from deadlock. 

Memory Management Strategies: Background, swapping, Memory allocation, Paging, Structure of the page table, Segmentation. Virtual Memory Management: Demand paging, Page replacement, allocation of frames, thrashing.

File concepts, access methods, directory and disk structure, File system mounting, File sharing, Protection, directory implementation, allocation methods, free-space management. I/O Systems, I/O hardware, Application I/O Interface.

[2] Robert Love, Linux System Programming, O’Reilly, 2014.

[2] Andrew S Tanenbaum & Herbert Bos, Modern Operating Systems, Pearson, 4th Edition, 2014.

ESE 50%

The course introduces fundamentals of programming, different types of problem-solving concepts and programming structures to build logic for suitable computational problems. 

Types of problems, Problem solving in every day, Difficulties in with problem solving. Constants, variables, data types, Data storage, operators, expressions. Organizing the solution, testing the solution, software development life cycle.

Structuring a solution, modules, cohesion and coupling, local and global variables, Algorithm, flowchart, pseudocode, Sequential logic structure, Solution Development.

The decision logic structure, Straight through logic structure, Positive logic, Negative logic, Logic conversion, Decision Tables. The loop logic structure, nested loops, recursion.

To enable the students to excel in the Linux Platform

RHEL7.5,breaking root password, Understand and use essential tools for handling files, directories, command-line environments, and documentation - Configure local storage using partitions and logical volumes

Swapping, Extend LVM Partitions,LVM Snapshot - Manage users and groups, including use of a centralized directory for authentication

Kernel updations,yum and nmcli configuration, Scheduling jobs,at,crontab - Configure firewall settings using firewall config, firewall-cmd, or iptables , Configure key-based authentication for SSH ,Set enforcing and permissive modes for SELinux , List and identify SELinux file and process context ,Restore default file contexts 

[2] https://access.redhat.com/documentation/en-US/Red_Hat_Enterprise_Linux/7

[2] https://access.redhat.com/documentation/en-US/Red_Hat_Enterprise_Linux/7

This course covers programming paradigms brought in by Python with a focus on Regular Expressions, List and Dictionaries. It explores the various modules and libraries to cover the landscape of Python programming.

Underlying mechanism of Module Execution- Sequences, Mapping and Sets- DictionariesFunctions - Lists and Mutability- Problem Solving Using Lists and Functions. Custom and built-in modules

Classes: Classes and Instances-Inheritance—Polymorphism- Abstract Classes-Exceptional Handling- Regular Expressions using “re” module.

Computation on NumPy-Aggregations-Computation on Arrays-Comparisons, Masks and Boolean Arrays-Fancy Indexing-Sorting Arrays-Structured Data: NumPy’s Structured Array. Introduction to Pandas Objects-Data indexing and Selection-Operating on Data in Pandas-Handling Missing DataHierarchical Indexing

Basic functions of Matplotlib-Simple Line Plot, Scatter Plot. Introduction to Tkiner module-Root Window-Widgets-Button-Label-Message-Text-Menu-Listboxes-Spinbox-Creating tables.

Introduction-Web framework-creating model to add database service- Django administration application. Basic Database Operations and SQL, Databases and Python, The Python DB-API, Connection Objects Databases and Python: Adapters Examples of Using Database Adapters, A Database Adapter Example Application.

[2] T. R. Padmanabhan, Programming with Python, Springer Publications, 2019.

To provide extensive knowledge of C programming language to the students. It helps in developing the ability to solve computational problems through programs. Lab component is included to give hands-on experience to the students. 

History of C - Memory concepts - Constants, variables, data types and keywords - Instructions and operators - Decision control structure - if… else construct - Loop control structure - For loop - While loop - Case control structure - Switch case - Break – Continue.

Functions - Library functions - Function definitions - Prototype - Scope - Storage classes -Call by value - Pointers variable - Definition and initialization - Pointer operators - Calling function by reference - Pointer arithmetic - Pointers to functions - Recursion - Recursion and stack.

Arrays - Definition - Initialization - 2D arrays - Memory map of 2D arrays - Pointers and 2D arrays - Pointers to arrays - Passing Arrays to functions - Array of pointers - Strings - Characters - Character handling library - String I/O - String conversion - String comparison - String search - Pointers and strings - Passing strings to functions. 

Structure definitions - Initializing structures - Accessing structure members - Array of structures - Pointers to structures - Using structures with functions - Self-referential structures - typedef - Unions - Bitwise operators - Bit fields - Enumeration constants.

Types of I/O - Formatted and unformatted console I/O functions - Printing integers, floats and strings - Conversion specifiers - Reading formatted input - Command line arguments - File processing - Data hierarchy - File and streams - File operations - Sequential-Access file - RandomAccess file - Error handling - Stderr - Exit A case study - Preprocessors - symbolic constants and macros - File inclusion - Conditional compilation.

[2] Byron Gottfried, Programming with C, McGraw Hill, 4th Edition, 2018. 

[2] Brian W. Kernighan, Dennis M. Ritchie, The C Programming Language, Pearson, 2nd Edition, 2012.

[3] Yashavant Kanetkar, Let us C, BPB, 17th Edition, 2020.

The Course provides solid fundamental knowledge of software engineering concepts to the students and it prepares them to develop the skills necessary to handle software projects. It also enables the students to apply software engineering principles to develop quality software applications.

A generic process model – Defining a framework activity, identifying a Task Set, Process - Prescriptive Process Models-Specialized Process Models. Requirements Engineering- Developing use cases, Elements of the requirements Model, Analysis pattern, negotiating requirements, validating requirements-Latest Methodology-RAD, DevOps, Fish Model, SCRUM AgileModeling.

The design process-Design concepts – Abstraction, Architecture, Patterns, Separation of concerns, Modularity, information hiding, Functional Independence, refinement, Aspects, Refactoring, Design classes, The design Model – Data Design elements, Architectural Design elements, Interface Design Elements, Component-Level Design elements, Deployment’s level Design elements.

Basic Design Principles, Component-level Design guidelines, Cohesion, Coupling, Functional design at the Component level, Designing traditional components–Component based developmentDomain Engineering, Component qualification, Adaptation, and Composition, Analysis and Design for reuse. User Interface Analysis and Design models

Software Quality- Software testing fundamentals- internal and external view of testing, White-box testing, Basic path testing - control structure testing - Black- box testing-Model Based Testing, Testing GUIs, Testing of Client-Server Architectures, Testing Documentation, testing for RealTime Systems.

Metrics in the process and project domains-Metrics for software quality, The project planning process, Software scope and Feasibility, Resources, software project estimation, Decomposition techniques- Empirical estimation models, COCOMO II Model, Software equation.

[2] Sommerville, Ian, Software Engineering, Addison Wesley, 9th Edition, 2011.

[2] Stephen R. Schach, Software Engineering, Tata McGraw-Hill Publishing Company Limited, 2007. 

Web Resources:

[1] www.nptel.ac.in 

ESE 50%

This course starts with an introduction to the basic concepts in research and leads through the various methodologies involved in the research process. It focuses on finding out the research gap from the literature and encourages lateral, strategic, and creative thinking. This course also introduces computer technology and basic statistics required for conducting research and reporting the research outcomes scientifically, with emphasis on research ethics.

Defining research problem: Selecting the problem- Necessity of defining the problem- Techniques involved in defining a problem- Ethics in Research.

Principles of experimental design- Working with Literature: Importance- finding literature- Using your resources- Managing the literature-Keep track of references- Using the literature- Literature review- On-line Searching: Database-SCI Finder- Scopus- Science Direct-Searching research articles- Citation Index -Impact Factor -H-index. 

Measurement of Scaling: Quantitative-Qualitative,-Classification of Measure scales- Data Collection- Data Preparation. 

Scientific Writing: Significance- Steps- Layout- Types- Mechanics and Precautions- Paper writing for international journals- Writing scientific report.  

Latex: Introduction-Text-Tables- Figures- Equations- Citations- Referencing and Templates (IEEE style)

[2] Zina O’Leary, The Essential Guide of Doing Research, 3rd Edition, SAGE Publications Ltd, 2017. 

[2] Kumar, Research Methodology: A Step by Step Guide for Beginners, 4th Edition, SAGE Publications Ltd, 2014.

ESE- 50%

To enable the students to incorporate knowledge in the architecture and functional modules of 8085 microprocessor. To dispense an exposure to various 8085 basic and advanced programming techniques.

Introduction to 8085

Introduction to Microprocessor 8085 –Signals -Address Bus, Data Bus. Block Diagram, Registers, Flags- Decoding and executing an instruction.

Introduction to 8085 programming

8085-programming model, Instruction Classification, Data Format and storage, 8085 instruction Set, Writing simple programs.

1. Write a program to add two 8-bit BCD numbers.

2. Write a program to add N-one byte numbers.

3. Write a program to multiply two 8 - bit numbers.

8085 Machine cycles and bus Timings -Addressing Modes- Data Transfer Operations -Arithmetic Operations- Logic Operations - Branch Operations.

1. Write a program to check whether a byte belongs to the 2-out-of-5 codes. Display FF if it is a 2-out-of- 5 code otherwise 00. (Number is 2-out-of-5 code if the left most three bits are zero and in the remaining five bits there are exactly two 1’s).

2. Write a program to find the first 10 terms of a Fibonacci sequence

3. Write a program to interchange N one bytes of data.

Additional data transfer and 16-bit Arithmetic Instructions, Arithmetic operations related to memory, Logic operations: Rotate, Compare, Counters and Time delays, Stack and Subroutines.

1. Write a program to perform linear search over a set of N numbers. Display FF if found otherwise display 00.

2. Write a program to add two 32 - bit binary numbers.

3. Write a program to sort the numbers in ascending and in descending using bubble sort.

4. Write a program to simulate a BCD counter to count from 0 to 100.

5. Write a program to check whether a one-byte number is a palindrome or not.

Control & status signals, Power supply and Frequency signals, Externally initiated signals, Serial I/O ports - ALU: Timing and Control Unit, Instruction Decoder, Serial I/O Control, Stack, PC, Address/Data Buffers.

1. Write a program to divide a 16 - bit number by an 8 - bit numbers.

2. Write a program to subtract a 16 - bit BCD number from another 16 – bit BCD number.

3. Write a program to simulate a stopwatch with a provision to stop the watch.

4. Write a program to display a rolling message.

Introduction – INTR, TRAP, RST 7.5, 6.5, 5.5 – RST, SIM and RIM instructions.

[2] Charles M Gilmore, Pal Ajit, Microprocessor Principles and Applications, Tata McGraw Hill, 2nd Edition, 2009.

ESE- 50%

On completion of this course, a student will be familiar with full stack and able to develop a web application using advanced technologies and cultivate good web programming style and discipline by solving the real-world scenarios.

Internet and web Technologies- Client/Server model -Web Search Engine-Web Crawling-Web Indexing-Search Engine Optimization and Limitations-Web Services –Collective Intelligence – Mobile Web –Features of Web 3.0-HTML vs HTML5-Exploring Editors and Browsers Supported by HTML5-New Elements-HTML5 Semantics-Canvas-HTML Media.

Self-Learning: Introduction to CSS3-CSS2 vs CSS3

XML-Documents and Vocabularies-Versions and Declaration -Namespaces JavaScript and XML: Ajax-DOM based XML processing Event-Transforming XML Documents-Selecting XML Data:XPATH-Template based Transformations: XSLT-Displaying XML Documents in Browsers - Evolution of AJAX -Web applications with AJAX -AJAX Framework

JavaScript Implementation - Use Javascript to interact with some of the new HTML5 apis -Create and modify Javascript objects- JS Forms - Events and Event handling-JS Navigator-JS CookiesIntroduction to JSON-JSON vs XML-JSON Objects-Importance of Angular JS in webAngular Expression and Directives-Single Page Application. 

Introduction to Node.js-REPL Terminal-Package Manager(NPM)-Node.js Modules and filesystemNode.js Events-Debugging Node JS Application-File System and streams-Testing Node JS with jasmine.

NODE JS WITH MYSQL Introduction to MySQL- Performing basic database operation(DML) (Insert, Delete, Update, Select)-Prepared Statement- Uploading Image or File to MySQL- Retrieve Image or File from MySQL.

Self-Learning: CRUD operation using MongoDB

Practical Exercises (45 Hours)

1. Identify a domain of your choice, list out ten entities in the domain. For each entity, identify minimum 10 attributes and assign the data type for each attribute with proper justification.

2. Develop static pages for a given scenario using HTML

3. Demonstrate Geolocation and Canvas using HTML5

4. Write an XML file and validate the file using XSD

5. Demonstrate XSL with XSD

6. Write a JavaScript program to demonstrate Form Validation and Event Handling

7. Create a web application using AngularJS with Forms.

8. CRUD Operation using AngularJS

9. Implement web application using AJAX with JSON

10. Demonstrate to fetch the information from an XML file (or) JSON with AJAX

11. Demonstrate Node.js file system module and Demonstrate Node.js file system module

12. Implement Mysql with Node.JS

[2] HTML 5 Black Book (Covers CSS3, JavaScript, XML, XHTML, AJAX, PHP, jQuery), DT Editorial Services, Dreamtech Press, 2nd Edition, 2016.

[2] Laura Lemay, Rafe Colburn & Jennifer Kyrnin, Mastering HTML, CSS & Javascript Web Publishing, BPB Publications, 1st Edition, 2016.

[3] Alex Giamas, Mastering MongoDB 3.x, Packt Publishing Limited, First Edition, 2017.

Web Resources:

[1] www.w3cschools.com

[2] http://www.php.net/docs.php 

To provide a strong foundation for database application design and development by introducing the fundamentals of database technology

Data models, schemas and instances, DBMS architecture and data independence, Database languages and interfaces, database system environment, Classification of DBMS. Using High-Level Conceptual Data Models for Database Design - Entity Types, Entity Sets, Attributes, and Keys - Relationship Types, Relationship Sets, Roles, and Structural Constraints - Weak Entity Types - ER Diagrams, Naming Conventions, and Design Issues – Relationship Types of Degree Higher than Two - Subclasses, Superclasses, and Inheritance – Enhanced Entity Relationship Model - Relational Database Design by ER- and EER-to-Relational Mapping – Role of Information Systems in Organizations - Database Design and Implementation Process.

Lab exercise:

1. Design ER diagram

SQL Data Definition and Data Types, Specifying Constraints in SQL, Basic Retrieval Queries in SQL, INSERT, DELETE, and UPDATE Statements in SQL, Additional features of SQL. Complex Queries, Triggers, Views, and Schema Modification More Complex SQL Retrieval Queries, Specifying Constraints as Assertions and Actions as Triggers, Views (Virtual Tables) in SQL, Schema Change Statements in SQL.

Lab Exercises:

2. Demonstrate use of DDL,DML commands and integrity constraints

3. Demonstrate usage of TCL commands

 Design Guidelines for Relation Schemas - Functional Dependencies - Normal Forms Based on Primary Keys - Second and Third Normal Forms - Boyce-Codd Normal Form – Multivalued Dependency and Fourth Normal Form - Join Dependencies and Fifth Normal Form – Inference Rules, Equivalence and Minimal Cover - Properties of Relational Decompositions - Nulls and Dangling Tuples - File Organization - Organization of Records in Files - Ordered Indices - B+ Tree Index Files - Static Hashing - Bitmap Indices. 

Lab exercises:

4. Data Retrieval using simple JOIN and referential integrity

5. Data Retrieval using OUTER, INNER JOINS 

 Transaction - Introduction to transaction processing- transaction and system concept- Desirable properties of transaction- Transaction support in SQL- concurrency control techniques – Two phase Locking techniques for concurrency- Concurrency Control Based on Timestamp Ordering. Recovery Concepts- NO-UNDO/REDO Recovery Based on Deferred Update- Recovery Techniques Based on Immediate Update- Shadow Paging.

Lab Exercises:

6. Sub Queries and Corelated queries

7. Views and Indexes

Distributed databases: Distributed Database concepts- Types - Data Fragmentation- ReplicationAllocation Techniques. Overview of Transaction Management - Overview of Concurrency Control and Recovery. 

Databases 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.

Lab Exercise :

8. Stored Procedures and Triggers

9. Basic operations on NOSQL DB

[2] O’neil Patric, O’neil Elizabeth, Database Principles, Programming and Performance, Argon Kaufmann Publishers, 2nd Edition, 2002.

[3] Ramakrishnan and Gehrke, Database Management System, McGraw-Hill, 3rd Edition, 2003.

ESE - 50%

This course aims to set the foundation for Data Communication in Networks by introducing the network components, topologies, network models, and important protocols based on the TCP/IP model for the internet.

Upon completing the course, the student will be:

- familiar with the basics of data communication;

- familiar with various types of computer networks;

- familiar about network components, topologies, network models, protocols and algorithms.

Introduction: Network Topology, Network Hardware, Network Software: Protocol Hierarchies, Design issues, Connection Oriented Vs Connection less, Service primitives, OSI Reference Model, TCP/IP, Wireless Transmission, Ethernet, Transmission Media, Digital Modulation and Multiplexing, Line codes, Switching.

Error Detection and Correction: Types of Error, Error Detection, Parity Check, The Internet Checksum, Cyclic Redundancy Check, Forward Error Correction. Data Link Control Protocols: Flow Control, Error Control, HDLC. ADSL, xDSL. Medium Access Control Sublayer: Static Channel Allocation, Assumptions for Dynamic Channel Allocation, Multiple Access Protocols – Aloha, CSMA, Collision free Protocols, Limited Contention Protocols. Ethernet, Wireless LANS, Repeaters, Hubs, Bridges, Switches, Routers, and Gateways. 

Routing Algorithms: The Optimality Principle, Shortest Path Algorithm, Flooding, Distance Vector Routing, Link State Routing, Hierarchical Routing, Link State Routing, Hierarchial Routing, Broadcast Routing, Multicast Routing.

The Network Layer in the Internet: IPv4 Protocol, IP Addresses, IPv6 Protocol, Internet Control Protocols - ARP, RARP, Label Switching and MPLS, OSPF Protocol, BGP Protocol.

Transport Service: Transport Service Primitives, Berkeley Sockets. Elements of Transport Protocols: Addressing, Connection Establishment, Connection Release, Error and Flow Control. 

The Internet Transport Protocols (UDP): Introduction to UDP, Remote Procedure Call, Real-Time Transport Protocols. The Internet Protocols (TCP): Introduction to TCP, TCP Service Model, TCP Segment Header, TCP Connection Establishment, TCP Connection Release, TCP Connection Management Modelling, TCP Sliding Window Protocol.

Electronic Mail, DNS and HTTP: Electronic Mail - SMTP and MIME, Electronic Mail - SMTP and MIME, Internet Directory Service -DNS, Web Access and HTTP. Internet Multimedia Support: Real-Time Traffic, Voice Over IP, Session Initiation Protocol, Real-Time Transport Protocol (RTP). Advanced Networks -Case study: IoT, Mobile Networks, SDN.

[2] Computer Networks, Andrew S. Tanenbaum, David J. Wetherall, Pearson New International, 5th Edition, 2014.

[2] Prakash C. Gupta, Data communications and Computer Networks, 1st Edition, 5th Reprint, PHI, 2009

Web Resources:

[1] https://www.geeksforgeeks.org/computer-network-tutorials

[2] https://www.tutorialspoint.com/data_communication_computer_network/index.htm

[3] https://www.guru99.com/data-communication-computer-network-tutorial.html 

ESE 50%

Introduction to Data Analytics course delivers the basics of analytics concepts and various techniques to discover new and hidden knowledge from the data set.

The course also covers the concepts of data mining algorithms that play a major part in the CRISP model.

This course provides insight into the complete research process in phases as research methodology, data exploration, modeling, evaluation and visualization.

R programming, Python programming, MATLAB and Excel are the suggestive tools for implementation.

Introduction; Data and Relations –Scales and measures; Data preprocessing - Data Transformation and Integration, Data Reduction. Additional Reading: Probability Distributions & Inferential Statistics.

Correlation - Linear Correlation, Correlation and Causality, Chi-Square Test; Regression - Linear Regression, Robust Regression, Neural Networks, , Cross Validation, Feature Selection. Additional Reading: Least Square Problems and Optimization.

Forecasting - Finite State-Machines, Recurrent Models, Autoregressive Models. Classification - Classificaiton Criteria - Naive Bayes Classifier - Linear Discriminant-Analysis - Nearest Neighbor Classifier - Decision Trees. Additional Reading: Stochastic and Kernel Methods.

Clustering - Clustering Partitions - Sequential Clustering - Prototype-based Clustering - Fuzzy Clustering -Relational Clustering - Cluster Tendency Assessment - Cluster Validity. Additional Reading: Mining Frequent Patterns. 

Visualization - Visualizing Amounts, Distributions, Proportions, x-y relationships, Geospatial Data, Uncertainty.Example Caselets: Dr Hans Gosling - Visualizing Global Public Health. Case Study Topics; Business Analytics and Healthcare analytics. Additional Reading: Open Source solutions from Kaggle, GitHub resources and Popular Research Labs. 

[2] Han, Jiawei; Kamber, Micheline and Pie, Jian, Data Mining Concept and Techniques, Morgan and Kaufmann Publisher, Third Edition, 2012.

[3] Wilke, Claus O., Fundamentals of Data Visualization A Primer on Making Informative and Compelling Figures, O’Reilly, 2019.

[2] Leskovec, Jure; Rajaraman, Anand; Ullman, Jeffrey D., Mining of Massive Datasets, Cambridge University Press, 2014. 

MSE:50%

This course aims at developing an understanding about the issues involved in defining and simulating perception, identifying the problems where AI is required and the different methods available, to compare and contrast different AI techniques available, to define and explain learning algorithms and to provide the student additional experience in the analysis and evaluation of complicated systems.

Introduction to AI, The Foundations of AI, AI Technique -Tic-Tac-Toe. Problem characteristics, Production system characteristics, Production systems: 8-puzzle problem. Intelligent Agents: Agents and Environments, Good Behavior: The concept of rationality – The nature of Environments, The Structure of Agents

Searching: Uninformed search strategies – Breadth first search, depth first search. Generate and Test, Hill climbing, simulated annealing search, Constraint satisfaction problems, Greedy best first search, A* search, AO* search. 

Propositional logic - syntax & semantics - First order logic. Inference in first order logic, propositional Vs. first order inference, unification & lifts, Clausal form conversion, Forward chaining, Backward chaining, Resolution.

Overview, Minimax algorithm, Alpha-Beta pruning, Additional Refinements. Classical planning problem, STRIPS- basic process and working of system

Introduction, Syntax processing, Semantic Analysis, Pragmatic and Discourse Description: Analysis - Perception. 

[2] S. Russell and P. Norvig, Artificial Intelligence A Modern Approach, 3rd Edition, Pearson Education, 2019.

[2] George F Luger, Artificial Intelligence Structures and Strategies for Complex Problem Solving, 4th Edition. Singapore: Pearson Education, 2008.

[3] N.L. Nilsson, Artificial Intelligence: A New Synthesis, 1st Edition, USA: Morgan Kaufmann, 2000

MSE 50%

To explore elementary data structures in computer science, and learn to implement them in C. The data structures include linked lists, stacks, queues, trees, heaps, hash tables, and graphs. It also introduces different techniques for searching, traversing trees, hashing, manipulating priority queues, sorting, finding shortest paths in graphs.

 Introduction to Pseudo code - Overview of Time & Space Complexity – Recursion – Abstract Data Type - Array - Stack - Queue - Linked lists - Traversing - Searching - Insertion - Deletion – Circular Linked list - Two-way Lists (Doubly) - Linked List Implementation of Stack and Queue - Application of stacks and Queues.

Lab Exercises:

1. Write a program to convert an infix expression to the postfix form.

2. Implement linked list and its operations.

Bubble Sort – Insertion – Selection – Quick – Merge – Linear Search – Binary search – Hashing – Chaining – Collision Resolution – Open Addressing – String Matching Algorithms: Naive, KMP

Lab Exercises:

3. Implement the concept of sorting technique

4. Implement the concept of searching/pattern matching technique

Representation of Graphs - Operations on Graphs - Depth First and Breadth First Search - Topological Sort - Minimum Spanning Tree Algorithms - Binary Tree - Traversing Binary Trees - Binary Heap - Priority Queue - Heap sort.

Lab Exercises:

5. Implementation of Minimum Spanning Tree

6. Implementation of BFS and DFS

Binary Search Trees - Searching, Inserting and deleting in Binary Search Trees - AVL Trees - AVL Balance Factor, Balancing Trees, AVL node structure, AVL Tree Rotate Algorithms

Lab Exercises:

7. Implementation of BST

8. Implementation of AVL Tree

B Trees – Operations on B Trees - B+ Trees - Red-Black Trees - Properties of Red-black Trees - Rotations - Insertion - Deletion operations

Lab Exercises:

9. Implementation of B Trees

10. Implementation of B+ Trees

[2] Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, Introduction to Algorithms, MIT Press, 3rd Edition, 2009

[3] Peter Brass, Advanced Data Structures, Cambridge University Press

[2] Yashavant Kanetkar , Data Structures Through C, BPB Publications, 2019.

[3] Robert Sedgwick, Kevin Wayne, Algorithms, Addison-Wesley Publishing Company. 4th Edition, 2011. 

ESE:50% marks

This course will help the learner to gain sound knowledge in object-oriented principles, GUI application design with database, and enterprise application design with Servlets.

·      Garbage Collection

·       the finalize () Method

·       Introducing Access Control

·       Understanding static

·      Introducing nested and inner classes

·       String class

·      String Buffer Class

·       Command Line Arguments.

Lab Exercises:

2. Implement the concept of class, data members, member functions and access specifiers.

Introduction to Object Oriented Programming (OOP)

·               Object-Oriented Programming (OOP) Principles

·               The Evolution of Java

·               Buzzwords of Java

·                Class

·               Declaring Objects

·               Introducing

·               Methods

·               Overloading methods

·               Constructors

·               Parameterized

·               Constructors

·               this Keyword

Lab Exercise:

1. Identify a domain of your choice, list out ten entities in the domain. For each entity, identify minimum 10 attributes and assign the data type for each attribute with proper justification.

·      Inheritance in java with Interfaces

·       Defining Interfaces

·       Implementing Interfaces

·       Extending Interfaces

·       Creating Packages

·      CLASSPATH variable

·      Access protection

·       Importing Packages

·       Interfaces in a Package.

Inheritance in Java

·      Inheritance Basics

·      Multilevel Hierarchy

·       Using super

·       Method overriding

·       Dynamic Method Dispatch

·       Abstract keyword

·      Using final with inheritance

·       the Object Class.

Lab Exercises:

3. Implement the concept of function overloading & Constructor overloading.

·      try-catch-finally mechanism

·       throw statement

·       throws statement

·       Built-in-Exceptions

·      Custom Exception

Lab Exercises:

4. Implement the static keyword – static variable, static block, static function and static class.

·      The Collections Overview

·      Collection Interface

·      List Interface

·      Set Interface

·      SortedSet Interface

·      Queue Interface

·      ArrayList Class

·      LinkedList Class

·      HashSet Class

·      Using an Iterator

·      The For Each Statement.

Lab Exercise:

10. Implement multithreading – Thread class, Runnable interface, thread synchronization and thread communication.

·      Generics Concept

·       General Form of a Generic Class

·       Bounded Types

·      Generic Class Hierarchy

·      Generic Interfaces

·       Restrictions in Generics.

Lab Exercises:

5. Implement String and String Buffer classes.

6. Implement this keyword and command line arguments.

·      Thread Model

·       Life cycle of a Thread

·       Java Thread Priorities

·       Runnable interface and Thread Class

·       Thread Synchronization

·       Inter Thread Communication.

·      Connecting to and querying a database

·       Automatic driver recovery

·       Connecting to the database

·       Creating a Statement for executing query

·       Executing a query

·       Processing a Query’s ResultSet

·      PreparedStatements.

Lab Exercises:

9. Implement Exception Handing in java.

Introducing GUI programming with Swing

·       Swing Basics

·       Components and Containers

·       JLabel and ImageIcons

·       JTextField

·       Swing Buttons

·       JTabbedPane

·       JScrollPane

·       JList – JComboBox – JTable – Swing Menus.

Lab Exercises:

11. Implement collection Interfaces and classes

·      Delegation Event Model

·       Event Classes

·       Key Event Class

·       Event Listener Interface

·       Adapter Classes

Lab Exercises:

7. Implement the concept of inheritance, super, abstract and final keywords.

8. Implement package and interface.

·      Interface

·       HttpServet Class

·       The Cookie Class

·       Handling HTTP GET Request

·       Handling HTTP POST Request.

Lab Exercises:

13. Implement Java Servlets

·      Servlets Basics

·       Life Cycle of a Servlet

·      A Simple Servlet,The Servlet API

·       Servlet Interfaces

·       Generic Servlet Class

·       HttpServletRequest Interface

·      HttpServeltResponse

Lab Exercises:

12. Implement basic CRUD operations in JDBC with SWING

ESE: 50% Marks

At the end of the semester, the students should develop the working project using Software Engineering, Web technologies, and Database concepts.

The objective of this course is to provide comprehensive understanding and ability to develop web applications with database systems by following software engineering methodologies.

ProjectOverview

RequirementSpecification

DetailedDesign(DatabaseandInterface)

Construction(Codingguidelines,Codequality)

Testing(Testcasesandtest results)

Submission

Presentation & Demonstration 

Presentation & Demonstration

ESE- 50%