psgr krishnammal college for women college of … · summer internship students will undergo summer...

M.ScCS 1

PSGR KRISHNAMMAL COLLEGE FOR WOMEN

College of Excellence

An Autonomous College - Affiliated to Bharathiar University

Reaccredited with ‘A’ Grade by NAAC

An ISO 9001:2008 Certified Institution

Peelamedu, Coimbatore – 641 004

M.Sc Computer Science

CURRICULUM AND SYLLABUS

(Effective from 2017-19 Batch onwards)

M.ScCS 2

M.Sc Computer Science

(Effective from the academic year 2017-19)

Programme Overview

PROGRAMME EDUCATIONAL OBJECTIVES

After few years from the completion of M.Sc programme, the students will be able to

Demonstrate expertise through significant technical accomplishments and professional skills

in industry

Exhibit continuous learning and research for the societal upliftment with human values and

ethics

PROGRAMME OUTCOMES

Upon completion of the programme, the students are expected to have acquired

Broad knowledge in core areas of computer science, current and emerging technologies in IT

Higher degree of technical skills in problem solving and application development

Analytical and managerial skills to enhance employment potential

Holistic development with strong emphasis on values and ethics

M.ScCS 3

Programme& Branch: M.Sc Computer Science

Curriculum and Scheme of Examination (2017-19 Batch) S

emes

ter

Pa

rt Subject

Code Title of paper

Examination

Marks

Credit

s

I III RDA1701 Paper 1: Design and

Analysis of Algorithms

4 56 4 3 40 60 100 4

I III MCS1702 Paper 2: Network

Security

4 56 4 3 40 60 100 4

I III ROO1703 Paper 3: Object Oriented

Software Engineering

4 56 4 3 40 60 100 4

I III RPH1704 Paper 4: PHP/MYSQL 4 56 4 3 40 60 100 4

I III RAD1705 Paper 5: Advanced

Database Management

Systems

4 56 4 3 40 60 100 4

I III RAD16P1 Lab 1: ADBMS Lab 5 75 - 3 40 60 100 3

I III RPH16P2 Lab 2: PHP / MYSQL

Lab

5 75 - 3 40 60 100 3

I III Online course - - - - - - - Grade

II III RNF1706 Paper 6: .Net Framework 4 56 4 3 40 60 100 4

II III MCS1707 Paper 7: J2EE

Programming

4 56 4 3 40 60 100 4

II III MCS1708 Paper 8: Distributed

Operating Systems

4 56 4 3 40 60 100 4

II III Elective – I 4 56 4 3 40 60 100 4

II III RNF16P3 Lab3: .Net Lab 5 75 - 3 40 60 100 3

II III MCS16P4 Lab4: J2EE

Programming Lab

5 75 - 3 40 60 100 3

II III MTH17A5 Interdisciplinary Course :

Statistical Techniques in

Practice

4 60 - 3 100 100 4

II III Online course - - - - - - - Grade

III III

MCS1709/

RD17E06 Paper 9: Data Mining

4 56 4 3 40 60 100

III III MCS1710

Paper 10: Wireless Networks 4 56 4 3 40 60 100

M.ScCS 4

III III RPY1711

Paper 11: Python

Programming 4 56 4 3 40 60 100 4

III III Elective – II 4 56 4 3 40 60 100 4

III III RRM17S1 Special Course: Research Methodology 4 60 - 3 - 100 100 4

III III MCS17P5 Lab 5: Data mining Lab 5 75 - 3 40 60 100 3

III III RPY17P6 Lab 6: Python Programming Lab 5 75 - 3 40 60 100 3

III IV Comprehensive Exam – Online - - 3 - - 100 Grade

III Summer Internship - - - - - - 100 Grade

III III Job Oriented Course - - - - - - - Grade

IV III MCS16PW Project Work and Viva- Voce 12 - - 20 80 100 12

IV III RIT1712

Advanced Learner Course 1 – Internet of Things - - - 3 - 100 100 5**

IV III RER1713

Advanced Learner Course 2 – Enterprise Resource Planning - - - 3 - 100 100 5**

M.ScCS 5

List of Electives

S. No Course

Code Course Title

1 RI17E01 Internet Protocols 2

RA17E02 Artificial Intelligence and Machine Learning 3 RC17E03/

MIT1710 Cloud Computing

4 RD17E04 Data analytics 5 RS17E05 Software Architecture 6 RS17E06 Soft Computing 7 RB17E07/

MIT1809 Big Data Analytics

8 RI17E08 Information Retrieval 9 RV17E09 Virtual Reality

List of online courses through open tutorials like spoken tutorial/ NPTEL / EDX /Coursera

/MOOC

S. No Course Title

1 Advanced C

2 Advanced C++

3 Linux

4 Netbeans

5 Selenium

6 Ruby

7 Perl

8 Python

9 R Programming

M.ScCS 6

SUMMER INTERNSHIP

Students will undergo summer internship during the second semester holidays from first week of

May to second week of June for a period of 4 weeks in a related organization approved by the

staff co - ordinator / HOD. It will be evaluated during III semester for 100 marks and converted to

equivalent grades as given below.

MARKS

Report : 50 Marks

Attendance : 10 Marks

Work Diary : 15 Marks Viva Voce : 25 Marks ---------------

100 Marks

Mark Range Grade Description

90 - 100 O Outstanding

80 - 89 D+ Excellent

75 -79 D Distinction

70 – 74 A+ Very Good

60 – 69 A Good

50 – 59 B Average

0 - 49 U Reappear

M.ScCS 7

Semester I

RDA1701 Design and Analysis of Algorithms Category L T P Credit

III 56 4 - 4

Preamble

This course covers the fundamental techniques for designing and analyzing algorithms, including

asymptotic analysis, Trees, graphs, divide and conquer algorithms and recurrences. It also presents

effective search methods, graph algorithms and randomized algorithms

Prerequisite

Data structures and algorithms

Course Outcomes

On successful completion of the course, the students will be able to

Mapping with Programme Outcomes

Cos PO1 PO2 PO3 PO4

CO1. S M M M

CO2. S M M M

CO3. S S M M

CO4. S M S M

CO5. S S S M

S- Strong; M-Medium; L-Low

CO

Number

CO Statement Knowledge

Level

CO1. Understand data structures and the concepts of algorithms for searching,

sorting and dynamic programming K2

CO2. Understand the proofs of algorithms K2

CO3. Demonstrate a familiarity with major algorithms and data structures K3

CO4. Apply appropriate algorithms and data structures for various applications K3

CO5. Analyze the computational complexity of various algorithms K4

M.ScCS 8

Syllabus

UNIT I (11 Hrs)

Introduction: Algorithms – Analysis of algorithms – Best case and worst case complexities,

Analysis of some algorithms using simple data structures, amortized time complexity.Binary search

trees: Searching – Insertion and deletion of elements – Analysis

UNIT II (12 Hrs)

AVL trees: Definition – Height – searching – insertion and deletion of elements, AVL rotations –

Analysis. Red black trees: Definition – searching – insertion and deletion of elements – algorithms

and their time complexities. Splay trees: Definition – Steps in Splaying – Analysis

UNIT III (11 Hrs)

Multi-way search trees: Indexed Sequential Access – m-way search trees – B-Tree – searching,

insertion and deletion - B+ trees - Tries Graphs: Definition – representations, Adjacency matrix,

packed adjacency list and linked adjacency list, – network representation – Graph search methods,

Breadth first Search and Depth first Search

UNIT IV (11 Hrs)

Divide and conquer: The General Method – Examples – Finding the Maximum and Minimum -

Merge sort - Quick sort - Binary Search. Greedy method: The General Method – Optimal Storage

on Tapes – Knapsack Problem – Job Sequencing with Deadlines – Optimal Merge Patterns -

Minimum cost spanning Trees – Single Source Shortest Path

UNIT V (11 Hrs)

Dynamic programming: The General Method – Multistage Graphs - All pairs shortest path problem

–Travelling sales Person problem. Back tracking: The General Method – The Eight Queen Problem

– Sum of Subset Problem – Graph Coloring – Hamiltonian Cycles

Text Book

Ellis Horowitz, SartajSahni and SanguthevarRajasekaran (2008). Fundamentals of Computer

Algorithms, 2/e, Universities Press Private Limited, India

Reference Books

1. Ellis Horowitz and SartajSahni (2003). Fundamentals of Data Structures, Gurgaon: Galgotia

Publication

2. Robert L Kruse(2008). Data Structures & Program Design, Prentice Hall, New Delhi

3. Tanenbaum A.M.(2008). Data Structures Using C, Prentice Hall of India, New Delhi

Pedagogy: Lectures, Discussion, Case study

Course Designers:

1.Mrs. V.Kalaimani

2.Mrs. S.Meera

M.ScCS 9

MCS1702 NETWORK SECURITY

Category L T P Credit

III 56 4 - 4

Preamble

This course presents the principles of cryptography and Network Security. It also includes the

classical and advanced encryption standards and techniques, message authentication codes, digital

signatures, email security, IP security, web security, firewalls and Mobile Network Security.

Prerequisite

Computer Networks

Course Outcomes


CO

Number


Level

CO1. Understand cryptography and network security concepts

and application

K2

CO2. Apply security principle in system design K3

CO3. Analyze network security protocols K4

CO4. Detect network security threat K5

CO5. Design the code to implement a cryptographic algorithm K6


COs PO1 PO2 PO3 PO4

CO1. S S M M

CO2. S S M S

CO3. S S M S

CO4. S S S S

CO5. S S S S


Syllabus

UNIT I (11 Hrs)

Introduction: Security Trends - The OSI Security Architecture - Security Attacks - Security

Services - A model for Internetwork Security. Classical Encryption Techniques: Symmetric Cipher

Model - Substitution Techniques -Transposition Techniques - Steganography

M.ScCS 10

UNIT II (12 Hrs)

Block Ciphers and the DES: Block cipher Principles - The DES - The Strength of DES -

Differential and Linear Crypt Analysis. Advanced Encryption Standard: Evaluation Criteria for

AES - The AES Cipher. Public key cryptography and RSA: Principles of Public – Key

Cryptosystems – The RSA Algorithm

UNIT III (11 Hrs)

Key management Other Public – Key Cryptosystems: Diffie-Hellman Key exchange – Elliptic

Curve Arithmetic - Elliptic Curve Cryptography. Message Authentication and Hash Functions:

Authentication Requirements - Authentication Functions - Security of Hash Functions and MACs

UNIT IV (11 Hrs)

Digital Signatures and Authentication Protocols: Digital Signatures - Authentication Protocols -

Digital Signature Standard. Authentication Applications: Kerberos - X.509 Authentication Service,

Public-Key Infrastructure. Email Security: Pretty Good Privacy - S/MIME

UNIT V (11 Hrs)

IP Security: IP Security Overview - IP Security Architecture - Authentication Header -

Encapsulating Security Payload. Web Security: Security Considerations - SSL and TLS-SET.

System Security: Intruders - Intrusion Detection – Password Management. Malicious Software:

Viruses and Related Threats. Firewalls: Design Principles - Trusted systems

Text Book

William Stallings (2007). Cryptography and Network Security - Principles and Practices, 4/e, New

Delhi: Prentice Hall of India

Reference Books

1. AtulKahate (2006). Cryptography and Network Security, Tata McGraw Hill, New Delhi

2. Charles P Pfleeger, Shari Lawrence P Pfleeger (2006). Security in Computing, 3/e, New

Delhi: Pearson education, New Delhi

3. BruiceSchneier (2008). Applied Cryptography – Principles, Algorithm and Source in C, 2/e,

Wiley India Pvt. Ltd, New Delhi.

4. Niels Ferguson, Bruce Schneier, Tadayoshi Kohno (2010). Cryptography Engineering–Design Principles and Practical Applications, Wiley India Pvt. Ltd. New Delhi

Pedagogy: Lectures, Demonstration, Video Lecture, Case Studies

M.ScCS 11

Course Designers

1. Mrs. R. Kowsalya

2.Dr. N. Radha

M.ScCS 12

ROO1703 OBJECT ORIENTED SOFTWARE

ENGINEERING


III 56 4 4

Preamble

This course provides methods and technologies involved in building complex software. It also introduces concepts that includes various steps involved in developing software including requirement elicitation, system design, object design and testing.

Prerequisite

• Software Engineering

• Object Oriented Concepts

Course Outcomes

On the successful completion of the course, students will be able to


COs PO1 PO2 PO3 PO4

CO1. S M M S

CO2. S M S S

CO3. S M M S

CO4. M S M S

CO5. M M S S


Syllabus

UNIT I (11 Hrs)

Introduction to Software engineering – Software engineering Failures – Software

EngineeringConcepts - Software Engineering Development Activities - Modelling with UML: An

Overview of UML - Modelling Concepts – A Deeper View into UML

CO

Number


Level

CO1. Understand the steps involved in developing the software. K2

CO2. Understand the roles and responsibilities of various persons involved in

development cycle. K2

CO3. Implement the methods and techniques to develop a small project. K3

CO4. Analyze the problems that may occur in each and every phase of software

development cycle. K4

CO5. Assess good standards to be followed to deliver successful software. K5

M.ScCS 13

UNIT II (11 Hrs)

Project Organization and Communication: Introduction - An Overview of Projects – Project

Organization Concepts - Project Communication Concepts - Organizational Activities Requirement

Elicitation: Introduction - An Overview of Requirement Elicitation Requirement Concepts -

Requirement Elicitation Activities - Managing Requirements Elicitation Analysis: Introduction - An

Overview of Analysis - Analysis Concepts – Analysis Activities: From Use Cases to Objects -

Managing Analysis

UNIT III (12 Hrs)

System Design: Decomposing the System – Introduction - An Overview of System Design - System

Design Concepts - System Design Activities: From Objects to Subsystems. System Design:

Addressing Design Goals - Managing system Design. Object Design: Reusing Pattern Solutions –

Introduction - An Overview of Object Design - Reuse Concepts-Reuse Activities. Testing:

Introduction - An Overview of Testing - Testing Concepts - Testing Activities

UNIT IV (11 Hrs)

Rationale Management: Introduction - An Overview of Rationale – Rationale Concepts - Rationale

Activities: From Issues to Decisions - Managing Rationale. Configuration Management: An

Overview of Configuration Management - Configuration Management Concepts - Configuration

Management Activities - Managing Configuration Management

UNIT V (11 Hrs)

Project Management: Introduction - An Overview of Project Management - Project Management

Concepts – Classical Project Management Activities – Agile Project Management

Activities.Software Life Cycle: Introduction- Life cycle processes-Characterizing Maturing of

Software Life Cycle Models-Life Cycle Models

Text Book

Bernd Bruegge and Allen H. Dutoit (2013). Object-Oriented Software Engineering: Using UML,

Patterns, and Java, Pearson Education, New Delhi.

Reference Books

1. David C. Kung (2013).ObjectOriented Software Engineering: An Agile Unified

Methodology, McGraw-Hill Higher Education.

2. Singh Yogesh (2012). Object – Oriented Software Engineering, PHI Publication.

3. Timothy C.Lethbridge and Robert Laganiere (2011). Object – Oriented Software

Engineering: Practical Software Development using UML and Java, Tata McGraw Hill.

Pedagogy: Lectures, Demonstration, Guest Lecture, Video Lecture, Discussion

M.ScCS 14

Course Designers:

1. Mrs. V. Santhana Lakshmi

2. Mrs. R. Kowsalya

M.ScCS 15

RPH1704 PHP/MYSQL Category L T P Credit

III 56 4 - 4

Preamble

This course introduces the concepts of PHP, HTML and MYSQL. It provides concepts of sessions

and cookies to develop web pages and the basics of data manipulation using MySQL database.

Prerequisite

HTML and C programming Language

Database Management System

Course Outcomes



Cos PO1 PO2 PO3 PO4

CO1. M M M M

CO2. M M M M

CO3. M M M M

CO4. S S S M

CO5. S S S M


Syllabus

UNIT I (11 Hrs)

Introduction: Server - Side Web Scripting - Syntax and Variables - Control and Functions. Passing

Information between Pages: GET Arguments - POST Arguments - Formatting Form Variables -

PHP Super global Arrays

CO

Number


Level

CO1. Understand the programming constructs of PHP Scripting

Language. K2

CO2. Understand the functions and concepts of PHP K2

CO3. Understand different web controls K2

CO4. Apply the connectivity between PHP and MYSQL database K3

CO5. Develop web pages using PHP, HTML and MYSQL K4

M.ScCS 16

UNIT II (12 Hrs)

String: Strings in PHP - String Functions-Arrays and Array Functions: Creating Arrays - Retrieving

Values - Multidimensional Arrays - Inspecting Arrays - Deleting from Arrays - Iteration. Advanced

Array Functions: Transformation of Arrays. Number Handling: Numerical Types - Mathematical

Operators - Simple Mathematical Functions - Randomness

UNIT III (11 Hrs) Regular Expressions: Tokenizing and parsing Functions - Regular Expressions - Perl - Compatible

Regular Expressions - Advanced String Functions. Working with the File system: PHP File

Permissions - File Reading and Writing Functions - File system and Directory Functions - Network

Functions - Date and time Functions - Calendar Conversion Functions. Working with Sessions and

Cookies: Sessions work in PHP - Session Functions - Configuration Issues - Cookies - Sending

HTTP Headers

UNIT IV (11 Hrs)

Structured Query Language (SQL): Relational Database and SQL - SQL standards - The

Workhorses of SQL - Database Design - Privileges and Security. PHP and MYSQL: Connecting to

MySQL - Making MySQL Queries - Fetching Data Sets - Multiple Connections - Error Checking -

Creating MySQL Databases with PHP - MySQL Functions

UNIT V (11 Hrs)

Performing Database Queries: HTML Tables and Database Tables - Complex mapping - Creating

the sample Tables. Integrating Web Forms and Databases: HTML Forms - Basic Form Submission

to a Database - Self Submission - Editing Data with an HTML Form

Text Book

Steve Suehring, Tim Converse and Joyce Park (2012). PHP6 and MySQL Bible, Wiley-India, New

Delhi.

Reference Books

1. Mike McGrath (2012). PHP and MySQL, McGraw Hill Education Private Limited, India.

2. Beighley(2011).Head First Php& MySQL, O'Reilly Publisher.

3. W. Jason Gilmore (2010).Beginning PHP and MYSQL: From Novice to Professional,

Dreamtech Press.

Pedagogy: Lectures, Presentations, Demonstrations, Guest Lectures

Course Designers:

1. Mrs. S.Kanagarathinam

2. Dr. N.Radha

http://www.amazon.in/Mike-McGrath/e/B00MCVM882/ref=dp_byline_cont_book_1

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Beighley&search-alias=stripbooks

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=W.+Jason+Gilmore&search-alias=stripbooks

M.ScCS 17

RAD1705

ADVANCED DATABASE

MANAGEMENTSYSTEMS


III 56 4 - 4

Preamble

This course presents the advanced concepts of Database Management Systems and various

databases like parallel, distributed and object oriented database management systems. The course

also introduces various advanced databases like Spatial and NoSQL databases.

Prerequisite

• DBMS Concepts

• SQL

• VB 6.0

Course Outcomes

On successful completion of the course, students will be able to


Cos PO1 PO2 PO3 PO4

CO1. S S M M

CO2. S S M M

CO3. S S M S

CO4. S S S S

CO5. S S S S


Syllabus

UNIT I (11 Hrs)

Parallel Database: Introduction - Architecture for Parallel Databases - Parallel Query Evaluation -

Parallelizing Individual Operations - Parallel Query Optimization

CO

Number


Level

CO1. Understand the concepts of parallel database, distributed database and

object oriented database K2

CO2. Understand the importance of data warehousing for decision support K2

CO3. Demonstrate various queries by applying RDBMS concepts K3

CO4. Analyze advanced databases like spatial and NoSQL databases for

handling data K4

M.ScCS 18

UNIT II (11 Hrs)

Distributed Database - Distributed DBMS Architectures - Storing Data in a Distributed DBMS -

Distributed Catalog Management - Distributed Query Processing - Updating Distributed Data -

Distributed Transaction - Distributed Concurrency Control - Distributed Recovery

UNIT III (11 Hrs)

Object Database System : Motivating Example - Structured Data Types - Operations on Structured

Data - Encapsulation and ADTs - Inheritance - Object, OIDs, and Reference Types - Database

Design for ORDBMS - ORDBMS Implementation Challenges - OODBMS - Comparing RDBMS,

OODBMS, and ORDBMS

UNIT IV (12 Hrs)

Data Warehousing And Decision Support: Introduction to Decision Support - OLAP:

Multidimensional Data Model - Multidimensional Aggregation Queries - Implementation

Techniques for OLAP - Data Warehousing - Data Warehouse Architecture - Data Warehouse

Implementation - Views And Decision Support - View Materialization - Maintain Materialized

Views - Data Mining : Introduction to Data Mining – Counting Co-occurrences – Mining for Rules

- Clustering – Similarity Search over Sequences

UNIT V (11 Hrs)

Advanced Databases: Information retrieval: Introduction - Indexing for Text Search - Web Search

Engines- Managing Text in a DBMS - Data Model for XML - XQuery. Spatial data management:

Types of Spatial Data and Queries - Applications Involving Spatial Data. NoSQL databases:

Introduction - Column oriented stores – Key - value stores - Document databases - Graph databases.

Introduction to Mapreduce and Hadoop

Text Book

1. Raghu Ramakrishnan and Johannes Gehrke (2007). Database Management System, 3/e,

McGraw Hill, Singapore.

2. G.K.Gupta (2011). Database Management systems, Tata McGraw Hill Private Limited.

3. Shashank Tiwari (2011). Professional NoSQL, John Wiley & Sons

Reference Books

1. Pranab Kumar Das Gupta, P. Radha Krishna (2013). Database Management System Oracle SQL and PL/SQL, PHI Learning Private Limited, New Delhi.

2. RiniChakrabarti, ShilbhadraDasgupta (2011). Advanced Database Management System, Wiley

India, Private Ltd.

3. Abraham Silberschatz et.al (2011). Database System Concepts, 6/e, McGraw Hill, Singapore.

4. Tom White (2012). Hadoop : The Definitive Guide, Third Edition,O’Reilly Media

Pedagogy: Lecture, Demonstration, Guest Lecture, Video Lectures, Discussion

Course Designer:

1. Mrs. S. Meera

2. Mrs. V. Preamsudha

M.ScCS 19

RAD17P1 ADBMS LAB Category L T P Credit

III - - 75 3

Preamble

This course provides implementation of object oriented, parallel and partitioning concepts in RDBMS packages. This course also covers various queries and mapreduce implementation in MongoDB.

Prerequisite

RDBMS

SQL

Oracle & MS-Access

Course Outcomes


CO

Number


Level

CO1. Understand the concepts of integrity constraints with some example

queries

K2

CO2. Implementing object oriented, parallel and partitioning queries K3

CO3. Demonstrate different queries in MongoDB K3

CO4. Apply the concepts of Mapreduce in MongoDB K4

CO5. Develop simple applications using VB with MS-ACCESS, ORACLE and

SQL K5


Cos PO1 PO2 PO3 PO4

CO1. S M M M

CO2. S M M M

CO3. S S M M

CO4. S M S M

CO5. S S S M


Syllabus

• Exercises to implement the concepts of null constraint, unique constraint, integrity

constraints, check constraints.

• Exercises to implement parallel queries.

• Exercises to implement the concepts of partitioning queries.

M.ScCS 20

• Exercises to implement object oriented concepts.

• Implement the various queries for CRUD operations in MongoDB.

• Exercises to apply the concepts of Mapreduce in MongoDB.

• Develop a simple application using ADODC with front-end as VB and MS-ACCESS as

back - end.

• Develop a simple application using ADODC with front-end as VB and Oracle as back-

end.

• Develop a simple application using ADODC with front-end as VB and SQL as back-end

connectivity.

Pedagogy: Demonstration

Course Designers

1. Mrs. S. Meera

2. Mrs. V. PreamSudha

M.ScCS 21

RPH17P2 PHP / MYSQL LAB


III - - 75 3

Preamble

This course provides exercises to implement features of PHP and MYSQL programming. It also

provides exercises to implement file concepts, regular expressions and web page designing using

PHP, HTML and MYSQL.

Prerequisite

• C Programming

• PHP / MYSQL

• HTML

Course Outcomes


CO

Number


Level

CO1. Implement the control functions K3

CO2. Apply the string functions K3

CO3. Implement the concepts of Regular Expression K3

CO4. Demonstrate the connectivity with MY SQL database K4

CO5. Develop web pages using PHP, HTML and MY SQL K4


Cos PO1 PO2 PO3 PO4

CO1. S S S M

CO2. M S S M

CO3. M S S M

CO4. M S S M

CO5. M S S M


M.ScCS 22

Syllabus

• Exercise to pass information between web pages using GET and POST methods.

• Exercise using arithmetic operations, String functions.

• Exercise to apply advanced string functions to manipulate strings.

• Exercise to implement file concepts to open, read, close and to delete a file.

• Exercise using Regular expressions for validation.

• Exercise to implement the date and time functions.

• Exercise to manipulate data using different queries.

• Exercise to implement explode and implode functions.

• Create data base connectivity between PHP and MYSQL.

• Create web pages with PHP and MYSQL database.

Pedagogy: Lectures, Presentations, Demonstrations, Guest Lectures

Course Designers:

1. Mrs. S. Kanagarathinam

2. Dr. N.Radha

M.ScCS 23

RNF1606 .NET FRAMEWORK Category L T P Credit

III 56 4 - 4

Preamble

This course presents the practical aspects of application development using .Net framework. It also

covers the Common Language Runtime (CLR), .Net framework classes, C#, and ADO.net

Prerequisite

• VB

• C++

Course Outcomes


CO

Number


Level

CO1. Understand the concepts of .Net framework Technology K2

CO2. Summarize the advantages and disadvantages of .Net framework K2

CO3. Demonstrate the C# console applications K3

CO4. Develop the web applications using C# K4

CO5. Design and develop the distributed data driven applications using .Net

framework K4


Cos PO1 PO2 PO3 PO4

CO1. S M M M

CO2. S M M M

CO3. S S M M

CO4. S M S M

CO5. S S S M


Syllabus

UNIT I (11 Hrs)

Evolution of Web Development: HTML Forms-Server Side and Client Side Programming.

Developing ASP.Net Applications – Visual Studio: Creating Websites- Designing a Webpage- The

anatomy of a Web form – Writing Code. Web Form Fundamentals: The anatomy of an ASP.Net

application – Introducing Server Controls – Improving the Currency Converter – A Deeper Look at

M.ScCS 24

HTML Control Classes – The Page Class. Web Controls: Steeping up to Web Controls – Web

Control Classes – List Controls – Table Controls – Web Control Events and AutoPostBack

UNIT II (12 Hrs)

State Management: The problem of State – View State – Transferring Information between Pages

– Cookies – Session State – Session State Configuration. Error Handling, Logging, and Tracing:

Common Errors – Exception Handling – Handling Exceptions – Throwing Your Own Exceptions –

Logging Exceptions – Error Pages – Page Tracing. Deploying ASP.Net Applications: ASP.Net

Applications and the Web Server – Internet Information Services(IIS) – Managing Websites with

IIS Manager – Deploying a Simple Site – Deploying with Visual Studio

UNIT III (11 Hrs)

C# Language: C# Languages Basics – Variables and Data Types – Variable operations – Object

based manipulation – Conditional Logic – Loops – Methods. Types, Objects and Namespaces:

Classes – Value types and reference types – Understanding namespaces and assemblies

UNIT IV (11 Hrs)

C#: Enumerators and Iterators – Exceptions - Serializing objects - Deep serialization-XML based

serialization - Multithreading – Interfaces and Structures - Delegates and Events – Indexers and

Properties

UNIT V (11 Hrs)

ADO.NET Fundamentals: Understanding Data Management – Configure database – SQL Basics -

ADO.Net basics – Direct Data Access – Disconnect Data Access. Data Binding: Single-Value data

binding

Text Book

1. Matthew MacDonald (2008), Beginning ASP.NET 3.5 in C#, 2/e; A press Berkeley

2. Jesse Liberty (2003), Programming Visual Basic .NET, 2/e; O’Reilly, Shroff Publishers

and Distributors Pvt. Ltd

Reference Books

1. Bill Evjen, Jason Beres (2009), Visual Basic .Net Bible, Hungry Minds Inc.

2. Herbert Schildt (2010), Complete Reference C#, Tata McGraw-Hill.

3. Joe Duffy(2010), Professional .Net Framework 2.0l, Wiley India.

Pedagogy: Lectures, Demonstrations, Discussions

Course Designers

1. Mrs.V.Kalaimani

2. Dr.N.Radha

M.ScCS 25

Preamble

This course presents concepts to design and develop web based and enterprise applications using J2EE. It also covers concepts such as JDBC, JSP, JNDI and struts framework.

Prerequisite

• Java

• HTML

Course Outcomes

On completion of the course, the students will be able to


COs PO1 PO2 PO3 PO4

CO1. S M M S

CO2. M S M S

CO3. M S M S

CO4. S S M S

CO5. S S M S


MCS1607 J2EE PROGRAMMING Category L T P Credit

III 56 4 - 4

CO

Number


Level

CO1. Understand the concepts of web designing using j2EE. K2

CO2. Understand the communication between application and database using JDBC API. K2

CO3. Apply JNDI concept to set up database connection pool. K3

CO4. Determine the importance of scripting language in making a web page interactive. K3

CO5. Analyze effective techniques to be followed to create a struts application. K4

M.ScCS 26

Syllabus

UNIT I (11 Hrs)

Understanding Java and J2EE Platform: Introduction: Examining the origin of J2EE, Application

Components, Roles – Working with the Model View Controller, Understanding J2EE API–

Introducing Application Servers: Implementing J2EE platform – features of Application server –

full J2EE Implementation – Partial J2EE Implementation – Studying Servlet Programming:

Magazine Publisher Application – Performing URL Redirection – Web.XML Deployment

Descriptor

UNIT II (12 Hrs)

JSP : Introduction to JSP –Working With JSP Tags – Scripting Tags – Implicit Objects – Directive

Tags – Enhancing the JSP tag Support : Custom Tag – Empty Tag –Simple Tag – JSP Expression

Language – Syntax of Expression Language – Types of Expression Language –Tag Attribute Types

– Resolving Expression Language –Expression Language Operators

UNIT III (11 Hrs)

JDBC: Introduction – Components – JDBC Architecture – JDBC API –New API- Major Classes

and Interfaces – Communicating with Data base by using JDBC APC – SQL 99 Data Types

UNIT IV (11 Hrs)

JNDI and Directory Services: Naming Services and Directory Services – Overview of X.500 and

LDAP – Reviewing JNDI Structure – Using JNDI and LDAP - Connecting to DNS – JNDI Service

Providers – Understanding J2EE Web services: Integrating J2EE and Web services – J2EE Web

Services

UNIT V (11 Hrs)

Struts Framework: Introduction to Struts – Development Models – Model View Architecture –

Enterstruts – Components of Struts – Building Simple Struts Application – Model Layer: Struts and

the model - Mini HR application - View Layer: Struts and view layer - View layer of mini

application. The Controller Layer: Struts and controller layer

Text Book

1. James MCGovern, Rahim Adaitia et.al, J2EE 1.4 Bible, WileyIndia Publications, NewDelhi.

2. SantoshKumar(2008), JDBC Servlets and JSP, 1/e, Dream tech Press.

3. James Holmes(2006), Struts – The Complete Reference, Tata Mc-Graw Hill Publications.

Reference Books

• Kogent Learning Solutions Inc (2014), Java Server Programming, Dreamtech Press.

• KishoriSharan(2014), Beginning javaAPIs JavaScript, JDBC, Apress.

• Kogent Learning Solutions Inc(2011), Java Server Programming Tutorial, Wiley India Private

Limited.

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Kogent+Learning+Solutions+Inc.&search-alias=stripbooks


http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Kishori+Sharan&search-alias=stripbooks



M.ScCS 27

Pedagogy : Lecture, Demonstration, Discussion.

Course Designers:

1. Mrs.V.Santhana Lakshmi

2.Mrs.V.Kalaimani

M.ScCS 28

MCS1608 DISTRIBUTED OPERATING

SYSTEMS


III 56 4 - 4

Preamble

This course introduces the architecture of distributed operating system. It also includes the techniques such as synchronization, scheduling, memory management and distributed web based system.

Prerequisite

• Operating System

• Data Structure

Course Outcomes



Cos PO1 PO2 PO3 PO4

CO1. S M M S

CO2. S S M M

CO3. S M M S

CO4. M S L S

CO5. S S M S


Syllabus

UNIT I (11 Hrs)

Introduction to Distributed System – Communication in Distributed Systems: Remote Procedure

Call - Synchronization in distributed system: Clock Synchronization – Mutual Exclusion –

Deadlocks in Distributed System

CO

Number


Level

CO1. Understand the architecture of distributed operating system. K2

CO2. Differentiate between centralized and distributed system. K2

CO3. Determine the difficulties of distributed memory management. K3

CO4. Analyze effective synchronization techniques to be performed to run a task

in a distributed system. K4

CO5. Evaluate the best methods to follow to execute a task in remote machines. K5

M.ScCS 29

UNIT II (11 Hrs)

Process and Processors in Distributed System : Threads – System Models – Processor allocation –

Scheduling in Distributed Systems – Fault Tolerance – Real Time Distributed System

UNIT III (12 Hrs) Distributed Object Based Systems: Architecture - Processes-Object Servers: Communication -

Distributed Objects: Binding a client to an objects – Static Versus Dynamic – Remote Method

Invocations – Parameter Passing – Naming: CORBA Object References – Globe Object Reference -

Synchronization – Consistency and Replication. Distributed File Systems: Distributed File System

Design – Distributed File System Implementation – File Usage – System Structure – Caching –

Replication –Trends in Distributed File System

UNIT IV (11 Hrs)

Distributed Shared Memory: Introduction – Shared Memory – Consistency Models – Page based

Distributed Shared Memory – Shared Memory – Shared Variable Distributed Shared Memory –

Object Based Distributed Shared Memory

UNIT V (11 Hrs)

Distributed Web Based Systems : Architecture – Processes – communication – Naming –

Synchronization – Consistency and Replication – Case Study : AMOEBA – Introduction –Objects

and Capabilities – Process Management – Memory Management – Communication

Text Book

1. Andrew S.Tanenbaum (2011). Distributed Operating System, 10/e, Pearson Education.

2. Andrew S.Tanenbaum (2011). MaartenVan Steen, Distributed System – Principles and

Paradigms, 2/e, Prentice Hall of India Pvt. Ltd.

Reference Books

1. ShubhraGarg(2013).Fundamentals of Distributed Operating Systems, S.K. Kataria& Sons,

2013.

2. YakupPaker et al (2012). Distributed Operating Systems: Theory and Practice, Springer.

3. S SKudate A P Kale et al(2012). Distributed Operating Systems, NiraliPrakashan.

Pedagogy : Lecture, Demonstration, Discussion.

Course Designers:

1. Mrs. V. Santhana Lakshmi

2. Mrs. T. Thendral

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Shubhra+Garg&search-alias=stripbooks

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Shubhra+Garg&search-alias=stripbooks

http://www.amazon.in/S-S-Kudate-A-P-Kale/e/B00OBR0M7E/ref=dp_byline_cont_book_1

M.ScCS 30

RNF16P3

. NET LAB


III - - 75 3

Preamble

This course presents the practical aspects of application development using fundamentals of ASP.

Net and C#. It also covers the concepts of web server controls, form validation, tracking and session

handling, Error handling, inheritance, delegates, file operations and ADO.net Connectivity

Prerequisite

C++

Course Outcomes



COs PO1 PO2 PO3 PO4

CO1. S M M S

CO2. S M M S

CO3. S S M M

CO4. S M S S

CO5. S S S M


Syllabus

• Exercises to build forms with web server control.

• Develop the applications using the validation controls. Design and develop the

application using the session tracking Design and develop the application using

the error handling.

CO

Number


Level

CO1. Implement the concepts of programming language K3

CO2. Implement the behavior of various objects and classes K3

CO3. Apply the decision and iteration control structures K3

CO4. Develop simple applications K4

CO5. Design and develop the applications using ADO.Net K4

M.ScCS 31

• Design and develop the applications using ADO.Net in ASP.Net

• Exercises using branching, loop statements, Interfaces & inheritance, Multiple

Exceptio ns, Delegates, and File operations.

• Design and develop the applications using ADO.Net in C#


Course Designers

1. Mrs.V.Kalaimani

2. Dr.Mrs.N.Radha

M.ScCS 32

Preamble

This course provides exercises to design and develop web based enterprise applications using J2EE.

It also provides exercises to implement JSP, Servlet and Struts concepts to create an interactive

application.

Prerequisite

• Java

• HTML

Course Outcomes

On completion of the course, the students will be able to


Cos PO1 PO2 PO3 PO4

CO1. S S M S

CO2. M S M S

CO3. M S M S

CO4. M S M S

CO5. S S M S


MCS16P4 J2EE PROGRAMMING LAB Category L T P Credit

III - - 75 3

CO

Number


Level

CO1. Understand the method of compiling and running a JSP program in

Netbeans. K2

CO2. Implement database connectivity techniques to connect application with the

database. K3

CO3. Apply struts tags to create a small application. K3

CO4. Apply exceptional handling techniques to develop an error free application. K3

CO5. Analyze the importance of web services in making a webpage interoperable. K4

M.ScCS 33

Syllabus

• Exercise to develop webpage to pass information between pages.

• Exercise to implement JDBC API to connect the application with the database.

• Exercise to design a website using form validation techniques.

• Exercise to implement arithmetic operations.

• Exercise to implement exception handling.

• Exercise to create an application using basic JSP tags.

• Exercise to develop a servlet application.

• Exercise to design a web application using struts.


Course Designers:

1.Mrs. V.Santhana Lakshmi

2. Mrs. V.Kalaimani

M.ScCS 34

Semester III

MCS1709/

RD17E06 DATA MINING

Category L T P Credits

III 56 4 - 4

Preamble This course presents the basic concepts of data mining, various data mining techniques like

classification, clustering, association rule mining. The course also introduces various applications

of data mining such as text mining, web mining, multimedia mining, image mining, spatial and

temporal mining and a data mining tool- WEKA

Prerequisite Database Management Systems Probability and Statistics

Course Outcomes On successful completion of the course, the students will be able to

CO CO Statement Knowledge

Number Level

CO1. Understand basic concepts of data mining K2

CO2.

Understand data mining techniques like classifications, clustering,

association rule mining, prediction and related algorithm K2

CO3. Apply data mining techniques to carry out simple data mining tasks K3

CO4. Implementing data mining algorithms using Tools K4

CO5. Assess the methods and techniques appropriate for the task K5

Cos PO1 PO2 PO3 PO4

CO1. S S M M

CO2. S S M M

CO3. S S S M

CO4. S S S M

CO5. S S S M


Syllabus

UNIT I (10 Hrs)

Introduction to data mining: Mining from database - Data mining functionalities – Mining patterns -

Classification of data mining systems - Major issues in Data mining.


M.ScCS 35

UNIT II (11 Hrs) Data Preprocessing: Need for preprocessing – Data summarization – Data cleaning – Data

integration - Data transformation – Data reduction – Data discretization

UNIT III (12 Hrs) Association Rule Mining: Apriori algorithm. Classification and Prediction - Decision trees - Naïve

Bayes - K Nearest Neighbour -Neural Networks - Support Vector Machine - Evaluation of

classification algorithms

UNIT IV (11 Hrs) Clustering: Cluster Analysis - Partitioning Methods - Hierarchical Methods - Density and Grid

based methods - Evaluation of clustering algorithms

UNIT V (12 Hrs) Advanced Data Mining Techniques: Mining Data Streams - Mining Time Series Data - Mining

Sequence Patterns in Biological Data - Graph Mining - Social Network Analysis – Spatial Data

Mining - Multimedia Data Mining - Text Mining - Mining the World Wide Web - Data Mining

Applications. Data mining tool – WEKA – Explorer – Preprocessing – Apriori algorithm-

Classification and Clustering algorithms

Text Book Jaiwei Han, Micheline Kamber (2006). Data Mining-concepts and techniques, 2/e, Morgan

Kaufmann Publishers, San Francisco

Reference Books

1. David Hand, Heikki Mannila and Padhraic Smyth (2001). Principles of Data Mining, Prentice

Hall of India, New Delhi

2. Mark A. Hall, Ian H. Witten, Eibe Frank (2011). Data Mining: Practical Machine Learning

Tools and Techniques, 3/e,Morgan Kaufmann Publishers, San Francisco

3. Arun K. Pujari (2001). Data Mining Techniques; Universities Press, Hyderabad

4. Soman KP (2005). Data mining from theory to practice,2/e, PHI Learning Pvt. Ltd., New Delhi

Pedagogy: Lectures, Demonstrations, Case studies

Course Designers:

1. Dr. M. S. Vijaya

2. Mrs. V. Pream Sudha

M.ScCS 36


MCS1710 WIRELESS NETWORKS

III 56 4 - 4

Preamble This course introduces the fundamentals of networking and principles of network operations. It

also provides knowledge on various generations of cellular systems. It also covers topics such

as satellite network, wide area network and personal area network.

Prerequisite Computer Networks TCP/IP


CO CO Statement

Knowledge

Number

Level

CO1. Understand the concepts of networking K2

CO2. Understand the principles behind the networking operation K2

CO3. Examine the services provided in various layers of networks K3

CO4. Classify different technologies followed in various generation of cellular

networks K3

CO5. Analyze different types of networks in wireless technology K4


Cos PO1 PO2 PO3 PO4

CO1. S S M M

CO2. S S M M

CO3. S S M M

CO4. S S S M

CO5. S S S M

S- Strong; M-Medium; L-Low Syllabus

UNIT I (11 Hrs)

Introduction to Wireless Networks: Evolution of Wireless Networks – Challenges. Wireless

Communications Principles and Fundamentals: The Electromagnetic Spectrum - Wireless

Propagation Characteristics and Modelling - Analog and Digital Data transmission - Modulation

Techniques for Wireless Systems - The Cellular Concept - Wireless Services. Principles of AIR-

Interface Design - Characteristics of the Wireless Medium.

M.ScCS 37

UNIT II (11 Hrs)

Generation of Cellular Systems: First Generation (1G) Cellular Systems - Second Generation (2G)

Cellular Systems: Introduction – D-amps – cdmaone - GSM – IS-41 - Third Generation (3G)

Cellular Systems: Introduction – 3G Spectrum Allocation – Service Classes and Application –

Fourth Generation (4G) Systems.

UNIT III ( 11 Hrs)

Principles of Wireless Network Operation: Network Planning – Wireless Network Operation -

Satellite Networks: Introduction - Satellite Systems - VSAT Systems - Examples of Satellite based

Mobile Telephony Systems - Satellite-based Internet Access.

UNIT IV (12 Hrs)

Fixed Wireless Access Systems: Wireless Local Loop versus Wired Access - Wireless Local Loop

- Wireless Local Loop Subscriber Terminals (WLL) - Wireless Local Loop Interfaces to the PSTN,

IEEE 802.16 Standards.Wireless Local Area Networks: Introduction - Wireless LAN Topologies -

Wireless LAN Requirements - The Physical Layer - The Medium Access Control (MAC) Layer -

Latest Developments. Wireless ATM: Introduction - Wireless ATM Architecture – HIPERLAN 2:

An ATM Compatible WLAN.

UNIT V (11 Hrs)

Personal Area Networks: Introduction to PAN Technology and Applications, Commercial

Alternatives: Bluetooth - Commercial Alternatives: HomeRF. Security Issues in Wireless Systems:

The Need for Wireless Network Security - Attacks on Wireless Networks - Security Services -

Wired Equivalent Privacy (WEP) Protocol - Mobile IP -Weaknesses in the WEP Scheme - Virtual

Private Network (VPN). Simulation of Wireless Network Systems.

Text Book

P.Nicopolitidis, M.S. Obaidat, G.I Papadimitriou, A.S. Pomportsis (2003). Wireless Network,

New Delhi: John Wiley & Sons (ASIA)

Reference Books

1. William Stallings (2002). Wireless Communication and Networks, Pearson Education, Delhi,

2. Kaveh Pahlavan, Prashant Krishnamurthy (2002), Principles of Wireless Networks - A

Unified Approach; 2/e; New Delhi: Pearson Education.

Pedagogy: Lectures, Group Discussions, Demonstrations, Simulation.

M.ScCS 38

Course Designers

1. Mrs.V. Santhanalakshmi

2. Mrs.R. Kowsalya

M.ScCS 39

Mapping with Program Outcomes

Syllabus


RPY1711 PYTHON PROGRAMMING

III 56 4 - 4

Preamble

This course introduces the concepts of programming in Python. It provides knowledge in core python,

advanced concepts like regular expressions, exception handling, multithreading, web programming

and data base programming

Prerequisite

• Basic understanding of Open source software

• Database concepts

Course Outcomes


CO

Number


Level

CO1. Understand the programming constructs of Python K2

CO2. Apply the concepts of Python in simple tasks K3

CO3. Develop web programming using Python K4

CO4. Create an application using database connectivity in Python K6

CO5. Create simple web applications using Python K6

Cos PO1 PO2 PO3 PO4

CO1 S S M M

CO2 S S S M

CO3 S S M M

CO4 S S S M

CO5 S S S M

Unit I (10 Hrs)

Introduction: What is Python? - Origins - Features - Getting started-Python Basics - Python

Objects - Numbers – Sequences - Strings, Lists and Tuples: - Strings - Strings and operators -

String only operators - Built-in functions - String - Built-in methods - Special features of

strings

Unit II (12 Hrs) Lists - Operators – Built in functions - List Type built-in methods - Special features of Lists,

Tuples - Operators and Built-in functions - Special features of Tuples – Mapping and setting

Dictionaries – Operators - Built-in and factory functions - Mapping types-built-in methods -

Dictionary keys.

M.ScCS 40

Unit III (11 Hrs) Set types- Operators - Built-in function - Set type built-in methods - Conditionals and loops.

Functions and functional programming – Modules - Objected oriented programming -

Execution environment

Unit IV (11 Hrs) Regular expressions - Multithreaded programming – Files & I/O: File objects – Built in

Functions – Methods – Built in Attributes – Standard files – Command line arguments – File

System – File Execution – Storage Modules. GUI Programming

Unit V (12 Hrs) Web programming- database programming - Exception Handling: Exception - Exception Handling - Except clause – Try- Finally clause - User Defined Exceptions

Text Book

1. Wesley J.Chun (2010). Core Python programming, 2/e, Pearson education.

Reference Books

1. Mark Lutz (2010). Programming Python, 4/e, O’Reilly Media.

2. Mark Summerfield (2009), Programming in Python 3, Pearson Education.

Pedagogy: Lectures, Demonstrations, Case studies

Course Designers:

1. Mrs. T.Thendral

2. Mrs.V.Santhanalakshmi

M.ScCS 41



RRM17S1 RESEARCH METHODOLOGY

III 56 4 - 4

Preamble

This course presents the concepts of research, types of research, research design, literature review

and writing reports. It also covers various areas of computer science.

Prerequisite

This course is most appropriate for post graduate students who are interested in research but do not have prior research experience.


CO CO Statement

Knowledge

Number Level

CO1. Understand the concepts of research design, research process and various

types of research K2

CO2. Understand the different steps in writing report K2

CO3. Implement the methods and techniques for experimental study K3

CO4. Analyze the ethical issues in research K4

CO5. Assess the Various research areas in Computer science K5

COs PO1 PO2 PO3 PO4

CO1. S M M M

CO2. S M M M

CO3. S S S M

CO4. S M S S

CO5. S S S S

S- Strong; M-Medium; L-Low Syllabus UNIT I (12 Hrs) Research - Definition- importance and meaning of research-characteristics of research – type of

research - steps in research. Research process – an overview. Identification of research area -

selection and formulation of research problem – formulation o f objectives. UNIT II (12 Hrs) Review of Literature – Course work - Literature Survey- Collecting research papers from journals - Web Browsing - Efficient Searching – Online Resources - Reading a research paper - Scopus tool - Develop a theoretical framework – Improve your methodology

M.ScCS 42

UNIT III (12 Hrs) Preparing the research design- Data collection and preparation – Experimental study – Result

analysis and Discussions - Writing a research paper – Publishing the results - IEEE format –

Latex tool.

UNIT IV (12 Hrs)

Significance of Report writing – Different steps in writing report – Layout of the researchreport- Types of Reports – Oral Presentation – Mechanics of writing a research report –Precautions for writing Research Reports.Ethical issues in research - Patent registration procedure

– Funding agencies - Writing research proposals – Effective presenting methods. UNIT V (12 Hrs) Various research areas in Computer science - Image processing – Networks and security- Data mining

and machine learning – wireless and sensor systems - Audio, speech, language and signal processing. Text Book

Kothari, C.R (2013), Research Methodology – Methods and Techniques, 2/e. Wiley Eastern Limited

Reference Books 1. R. Panneerselvam (2014), Research Methodology, 4/e. Prentice Hall India Learning

Private Limited. 2. Ranjit Kumar (2011), Research Methodology – A step- by-step guide for beginners,

3/e. Pearson Education. 3. Deepak Chawla and Neena Sondh (2011), Research Methodology, Concepts and Cases,

Vikas Publishing House Pvt. Ltd.

Pedagogy: Lectures, Demonstration, Case Studies

Course Designers: 1. Mrs. T. Thendral 2. Mrs.S.Meera

M.ScCS 43

DATA MINING LAB


MCS17P5 III 56 4 - 4

Preamble This course provides exercises to implement data mining techniques such as classification, clustering,

association rule mining, regression using data mining tool like R. It also covers working with NoSQL

databases.

Prerequisite

SQL, Oracle Course Outcomes On successful completion of the course, students will be able to

CO CO Statement

Knowledge

Number

Level

Implement the association rule mining, classification, clustering, prediction K3

CO1. algorithm using R tool.

CO2. Apply data mining techniques to real world problem K3

CO3.

Analyze the performance of various classification, clustering and prediction

algorithm K4

CO4. Evaluate the features of data mining tools. K5

CO5. Create database using MongoDB and perform MapReduce operations K6


Cos PO1 PO2 PO3 PO4

CO1. S S S M

CO2. S S S M

CO3. S S S M

CO4. S S S M

CO5. S S S M

S- Strong; M-Medium; L-Low Syllabus Exercises to implement visualization techniques in R

Exercises to implement correlation, linear regression in R

Exercises to perform classification in R

Exercises to perform clustering in R

Exercises to perform association rules in R

Exercises to perform text mining in R.

Exercises to apply MapReduce for document collections in MongoDB Pedagogy: Demonstrations

Course Designer: 1. Mrs. V.Pream Sudha 2. Mrs. S.Meera

M.ScCS 44


RPY17P6 PYTHON PROGRAMMING LAB


III 56 4 - 4

Preamble This course introduces the concepts of programming in Python. It provides technical skill in core

python, advanced concepts like regular expressions, exception handling, multithreading, web

programming and data base programming.

Prerequisite • C++ & Java

• SQL

• Oracle & MS-Access Course Outcomes


CO

Number


Level

CO1. Understand the basic concepts of python programming K2

CO2. Implementing the object oriented concepts to improve

reusability.

K4

CO3. Apply python concepts to develop applications that solves

industrial problem.

K4

CO4. Compare python programming language with other languages K5

CO5. Develop simple web application K5

COS PO1 PO2 PO3 PO4

CO1. S S S M

CO2. S S S M

CO3. S S S M

CO4. S S S M

CO5. S S S M

S- Strong; M-Medium; L-Low Syllabus

1. Exercises to implement File handling concept

2. Exercises to implement list

3. Exercises using Dictionary.

4. Exercises to perform set operations.

5. Exercises using object oriented concepts.

6. Exercises to perform operations using Regular expression.

7. Exercises using exceptional handling technique.

8. Exercises using multithreading.

9. Exercises to perform operations on Byte objects.

10. Create an application using python with database connectivity.

M.ScCS 45


1. Mrs. V.Santhana Lakshmi

2. Mrs. T. Thendral

Course Designers

M.ScCS 46

SEMESTER IV

RIT1712 ADVANCED LEARNER COURSE 1 – INTERNET OF

THINGS


III - - - 5

Preamble This course covers the fundamentals of Internet of Things, methodologies and protocols.

The course also includes tools such as Arduino, Raspberry Pi and Galileo Prerequisite Computer Networks Internet Protocol


CO CO Statement

Knowledge

Number

Level

CO1. Understand the fundamentals of Internet Things K2

CO2.

Design a portable IoT using Ardunio / equivalent boards and

relevant protocols K3

CO3. Analyze applications of IoT in real time scenario K4

CO4. Develop web services to access /control IoT devices K5

CO5. Deploy an IoT application and connect to the cloud K6


COs PO1 PO2 PO3 PO4

CO1 S S M M

CO2 S S S M

CO3 S S S M

CO4 S S S M

CO5 S S S S


Syllabus

UNIT I Fundamentals of IOT: Introduction-Characteristics-Physical design - Protocols – Logical

design – Enabling technologies – IoT Levels – Domain Specific IoTs – IoT vs M2M.

UNIT II IOT design methodology: IoT systems management – IoT Design Methodology –

Specifications Integration and Application Development.

M.ScCS 47

UNIT III Building IOT with RASPBERRY PI : Physical device – Raspberry Pi Interfaces –

Programming – APIs / Packages – Web services.

UNIT IV Building IOT with GALILEO/ARDUINO : Intel Galileo Gen2 with Arduino-

Interfaces - Arduino IDE – Programming - APIs and Hacks.

UNIT V Case studies and advanced topics: Various Real time applications of IoT-

Connecting IoT to cloud – Cloud Storage for Iot – Data Analytics for IoT –

Software & Management Tools for IoT.

Text Books 1. Arshdeep Bahga, Vijay Madisetti (2015). Internet of Things – A hands-on approach;

Hyderabad: Universities Press

2. Manoel Carlos Ramon (2014).Intel® Galileo and Intel® Galileo Gen 2: API Features and

Arduino Projects for Linux Programmers; United States of America: Apress

Reference Books 1. Honbo Zhou (2012). The Internet of Things in the Cloud : A Middleware Perspective;

New York : CRC Press .

2. Dieter Uckelmann; Mark Harrison; Florian Michahelles (Eds.) (2011). Architecting the

Internet of Things; Germany: Springer.

3. David Easley and Jon Kleinberg (2010). Networks, Crowds, and Markets:

Reasoning About a Highly Connected World; United Kingdom: Cambridge University

Press.

4. Olivier Hersent, Omar Elloumi and David Boswarthick (2012). The Internet of Things:

Applications to the Smart Grid and Building Automation ; United States : Wiley

Publishing Inc

Course Designers

1. Mrs. R. Kowsalya 2. Mrs. V. Santhanalakshmi

M.ScCS 48

ADVANCED LEARNER COURSE 2:


RER1713

ENTERPRISE RESOURCE PLANNING

III - - - 5

Preamble

This course contains the Business process reengineering, ERP life cycle and ERP related

Technologies. This will also offer the technologies involved in business modules in ERP packages. It

also covers the emerging trends in ERP case studies.

Prerequisite Data base concepts Software Project Management


CO


Number

Level

CO1.

Understand the concepts of ERP Technologies, Business process K2

reengineering and Data Mining concepts.

CO2. Understand the concept of ERP Life cycle and Project Management K2

CO3. Identify the various Business modules in ERP Packages K3

CO4. Analyse the ERP market place of SAP, Oracle and SSA K4

CO5. Analyse the ERP Packages in manufacturing, textile, and e-commerce K4

Mapping with Programme Outcome

COS PO1 PO2 PO3 PO4

CO1. S M S M

CO2. S M M M

CO3. S M S M

CO4. M M S S

CO5. S M M S


Syllabus

UNIT I ERP: An Overview, Enterprise – An Overview, Benefit s of ERP - ERP and Related Technologies - Business Process Reengineering (BPR) - Data Warehousing - Data Mining - OLAP, SCM.

UNIT II ERP Implementation Lifecycle - Implementation Methodology - Hidden Costs - Organizing the Implementation – Vendors, Consultants and Users - C ontracts with Vendors - Consultants and Employees - Project Management and Monitoring. UNIT III Business modules in an ERP Package – Finance – Manu facturing - Human Resources - Plant Maintenance - Materials Management - Quality Management - Sales and Distribution.

UNIT IV ERP Market Place - SAP AG – PeopleSoft – Baan - JD Edwards – Oracle – QAD - SSA

M.ScCS 49

UNIT V ERP Case Studies: Post implementation review of ERP Packages in Manufacturing - Services and Textiles - Turbo Charge the ERP System - EIA, ERP and e-Commerce - ERP and Internet, Future Directions. Text Book Alexis Leon (2014). ERP Demystified, Tata McGraw-Hill, New Delhi.

Reference Books 1. K. Ganesh et al (2014).Enterprise Resource Planning: Fundamentals of Design and

Implementation, Springer Publication 2. D P Goyal (2011). Enterprise Resource Planning A Managerial Perspective, McGraw Hill Education

(India) Private Limited 3. Rajesh Ray. (2010). Enterprise Resource Planning, McGraw Hill Education (India) Private Limited

Course Designers

1. Mrs.V.Kalaimani 2. Mrs.S.Meera

M.ScCS 50

Electives

RI17E01 INTERNET PROTOCOLS


III 56 4 - 4

Preamble

This course presents the concept of protocols in the TCP/IP suite, voice video over IP (RTP),

Routing Architectures. It also includes Internet Application Services such as domain name system

(DNS), Electronic Mail(SMTP,MIME), File Transfer and Access (FTP,TFTP, NFS), Remote login(TELNET, rlogin) and Network Management (SNMP), a description of private network

interconnections such as NAT and VPN.

Prerequisite

Computer Networks

Basic Concept of Networking

Course Outcomes


CO

Number


Level

CO1.

Understand concept of protocols in the TCP/IP suite, voice video over

IP(RTP), Routing Architectures. K2

CO2. Apply the routing concept in the given topologies. K3

CO3. Analyze the relation between the various internet protocols K4

CO4.

Evaluate the suitability of an internet protocol for supporting a given

application type K5

CO5. Construct the alternate protocol K6


Introduction and Overview: The TCP/IP Internet - Internet Services - History and Scope Of The

Internet - Two Approaches to Network Communication - Wide Area and LAN - Ethernet

Technology - Switched Ethernet - Asynchronous Transfer Mode - Internetworking Concept and

Architectural Model: Application-Level Interconnection - Network -Level Interconnection -

Internet Architecture - Interconnection through IP Routers

COs PO1 PO2 PO3 PO4

CO1. S M M S

CO2. S M M S

CO3. S S S S

CO4. S S S S

CO5. S S S S


Syllabus

UNIT I (12 Hrs)

M.ScCS 51

UNIT II (11 Hrs)

Classful Internet addresses - Mapping Internet Addresses of Physical Addresses (ARP) - User Datagram Protocol (UDP)

UNIT III (11 Hrs) Internet Protocol: Connectionless Datagram Delivery (IPv4), Forwarding IP Datagram, Error and

Control Messages (ICMP)

UNIT IV (11 Hrs) Routing Between Peers (BGP), Routing Within an Autonomous System (RIP, OSPF), Mobile IP,

Private Network Interconnection (NAT, VPN)

UNIT V (11 Hrs) World Wide Web (HTTP), Voice and Video Over IP (RTP, RSVP, QOS), A Next Generation IP

(IPv6).

Text Book

Douglas E. Comer (2006). Internetworking with TCP/IP Principles, Protocols and Architecture, 5/e, New Delhi, Prentice Hall India

Reference Books

1. Behrouz A. Forouzan (2006). TCP/IP Protocol Suite,1, Tata McGraw Hill, New Delhi

2. Richard Stevens (2003). TCP/IP Illustrated, Volume 2, Prentice Hall of India, New Delhi

3. Julie C. Gaffin (2007). Internet Protocol 6, Nova Science Publisher Inc., Newyork

Pedagogy: Lectures, Case Studies, Group discussions

Course Designers

1. Mrs. R. Kowsalya

2. Dr. N. Radha

M.ScCS 52

Syllabus

RA17E02 ARTIFICIAL INTELLIGENCE AND Category L T P Credit

MACHINE LEARNING

III 56 4 - 4

Preamble This course presents the fundamentals of knowledge representation for problem solving, learning

methods of Artificial Intelligence and the deeper concepts of Machine Learning and Algorithms. It

also covers various Statistical, Reinforcement, supervised and unsupervised learning algorithms used

for classification, prediction and clustering and Case studies.

Prerequisite

Mathematical Logic, Linear Algebra and Calculus


CO

Number


Level

CO1. Understand the real world problems using state space representation , Concepts

of Machine Learning Algorithms

K2

CO2. understand the strengths and weaknesses of different problem solving techniques K2

CO3. Apply Artificial Intelligence and Machine Learning Techniques to solve real

world problems K3

CO4. Analyse the applicability of different heuristic techniques for problem solving K4

CO5 Create models for real world problems using Machine Learning Algorithms K6



Unit I (11 Hrs) Introduction: Definition of AI - AI Problems – Topics of AI – Production Systems – State space

Representation - Applications of AI

Unit II (11 Hrs) Heuristic Search Techniques: Generate and Test - Hill Climbing - Search techniques - Problem Reduction

– Constraint Satisfaction – Means –end- Analysis

Unit III (11 Hrs)

Game Playing:MINIMAX Procedure – ALPHA-BETA Pruning – Combined Approach Knowledge

representation: – Knowledge Management – types of Knowledge – Knowledge representation –

Approaches to knowledge Representation - Issues in Knowledge representation – Reasoning

Cos PO1 PO2 PO3 PO4

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M.ScCS 53

Unit IV (12 Hrs)

Learning –Association Learning - clustering: K-means clustering – Fuzzy clustering - Hierarchical

Clustering – Reinforcement Learning: Markov Decision Problem - Q- Learning – Learning Automata –

Statistical Learning: Hidden Markov Models – Linear Classifiers – Quadratic Classifiers –Decision Trees

– Bayesian Networks

Unit V (11 Hrs)

Supervised Learning: Support Vector - Case-based Reasoning – Ensemble Classifiers - Nearest

Neighborhood – Unsupervised Learning: Expectation maximization – Self organizing Maps - Adaptive

Resonance Theory

Case Studies - clustering, Reinforcement Learning, Statistical Learning, Unsupervised Learning

Text Book 1. S.S. Vinod Chandra, S. Anand Hareendran (2014). Artificial Intelligence and machine Leaning,

Eastern Economy Edition, PHI Learning Private Limited, New Delhi.

Reference Books

1. Elaine Rich and Kevin Knight (2009). Artificial Intelligence, 3/e, Tata McGraw Hill, New Delhi.

2. Donald A. Waterman (2003). A Guide to Expert Systems, Tech knowledge Series in Knowledge

Engineering, New Delhi

3. Charnaik, E., C.K. Reiesbeck, and D.V. McDermett (2000). Artificial Intelligence Programming,

Lawrence Erlbaum Associates, New Jersey

4. Stephen Marsland(2009). Machine Learning: An Algorithmic Perspective, Chapman and Hall,

2009.

5. Christopher Bishop(2007). Pattern Recognition and Machine Learning, Springer

Pedagogy:

Class room lectures, Group Discussion, Demonstrations

Course Designers: 1. Dr. N.Radha 2. Mrs.V.Pream Sudha

M.ScCS 54

RC17E03/

MIT1710 CLOUD COMPUTING


III 56 4 - 4

Preamble This course introduces the student to gain knowledge on various services of cloud computing. It also presents cloud computing collaborations and applications. It presents new concept of virtualization.

Prerequisite

Computer Networks Web Technology

Course Outcomes On successful completion of the course, students will be able to


Number Level

CO1. Understand the concepts of cloud Architecture and its services. K2

CO2. Classify different services providers and its services, tools. K3

CO3. Demonstrate various web based applications for collaborating everyone in K3

the cloud computing.

CO4. Analyze the best service provider for cloud computing in terms of storage, K4

services.

CO5. Assess various industrial platforms for the developments K5


COs PO1 PO2 PO3 PO4

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Syllabus

UNIT I (11 Hrs) Introduction: Benefits and Limitations-Cloud Architecture – Storage – Services –Service Providers - Types of Cloud Service Development – Services and Tools

UNIT II (12 Hrs) Collaborating on Contact Management - Collaborating on Project Management- Collaborating on

Word Processing, Spreadsheet, Presentations, Databases- Sharing Files and Photographs

UNIT III (11 Hrs) Cloud Virtualization Technology –Virtualization Defined–Virtualization Benefits – Server

Virtualization – Virtualization for x86 Architecture – Hypervisor Management Software – Logical

Partitioning – VIO Server – Virtual Infrastructure Requirements

M.ScCS 55

UNIT IV (11 Hrs) Deep Dive: Cloud Virtualization –Introduction - Storage Virtualization–Storage Area Networks–Network Attached Storage – Cloud Server Virtualization – Virtualized Data Center

UNIT V (11 Hrs) Industrial platforms and new developments - Amazon web services: Compute services - Storage

services - Communication services - Additional services - Google AppEngine: Architecture and core

concepts - Application life cycle - Cost model Microsoft Azure: Azure core concepts - SQL Azure -

Windows Azure platform appliance

Reference Books

1. Michael Miller (2011). Cloud Computing: Web-Based Applications That Change the Way You

Work and Collaborate Online, Pearson publication.

2. Dr. Kumar Saurabh (2011). Cloud Computing : Insights into New Era Infrastructure, Wiley

India

3. Rajkumar Buyya, Christian Vecchiola, S. Thamarai Selvi (2013). Mastering Cloud Computing

Foundations and Applications Programming, Morgan Kaufmann is an imprint of Elsevier

4. Rishabh Sharma (2014). Cloud Computing: Fundamentals, Industry Approach and Trends,

wiley India edition.

5. Paul Mehner (2013). Cloud Computing with the windows Azure Platform, Microsoft Press US

Pedagogy: Lectures, Case Studies, Group Discussions

Course Designers

1. Mrs. S. Meera 2. Mrs. V. Kalaimani

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Rishabh+Sharma&search-alias=stripbooks

http://www.amazon.in/Paul-Mehner/e/B00E7N18R0/ref=sr_ntt_srch_lnk_3?qid=1429802920&sr=8-3

M.ScCS 56

RD17E04 DATA ANALYTICS


III 56 4 - 4

Preamble This course presents the different methods for analysing data to enable decision making. It also introduces Macro programming and R tool for data analytics.

Prerequisite

MS - Excel Statistics



Number Level

CO1. Understand various spreadsheet functions available for data analytics and K2

management

CO2. Apply statistical and financial functions for decision making K3

CO3. Demonstrate data analysis and visualization using R tool K3

CO4. Analyse voluminous data and derive knowledge using appropriate functions K4

CO5. Develop Excel macros in Visual Basic Applications for analysing data K4


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Syllabus

UNIT I (11 hrs) Introduction to Spreadsheet -Basic Functions- Time and date functions - Sort - Filter- Conditional Formatting

UNIT II (11 hrs) Analysis using Functions: Text Functions - look up function - match functions - index functions - Statistical and Financial Functions – What if analysis, Solver - Sum product

UNIT III (11 hrs) Data Management and Modelling – Evaluating data- summarization – consolidating data – Correlation - Regression – Forecasting - Analysis of Variation with Moving average

M.ScCS 57

UNIT IV (12 hrs) Excel Macros (VBA) – Beginning Programming with VBA - Variables, data types, constants-Input and Output with VBA- String Manipulation – Event Procedures-Function Procedures- Looping-Arrays

UNIT V (11 hrs) Analytics with R: Introduction-Data with R- Objects-Reading and saving files - data types –Working with objects - Statistical analysis with R : t-test - Correlation – Covariance - Simple linear regression - Graphics with R-Basic boxplots - scatterplots- Line charts- Piecharts

Text Book 1. Wayne L Winston (2004). Microsoft Excel Data Analysis and Business Modelling, Microsoft

Press 2. Duane Birnbaum, Michael Vine (2007). Microsoft Excel VBA Programming for the Absolute

Beginner, Third edition, Thomson Press. 3. Mark Gardener (2012). Beginning R: The Statistical Programming Language, John Wiley India

Publishing

Reference Books

1. Stephen L.Nelson, Elizabeth C.Nelson(2016). Excel Data analysis for Dummies, 3/e, John Wiley

& Sons 2. John Walkenbach(2013). Excel VBA Programming for Dummies, Third edition, John Wiley &

Sons 3. Michael J.Crawley(2005). Statistics: An Introduction using R, John Wiley & Sons

Pedagogy: Lectures, Demonstrations, Group Discussions

Course Designers: 1. Mrs. V.Pream sudha 2. Dr. M. S. Vijaya

M.ScCS 58

RS17E05 SOFTWARE ARCHITECTURE Category L T P Credit

III 56 4 - 4

Preamble

This course provides the concepts of Software architecture, analysis method, architecture reviews

and architecture based development. This course also introduces the design of software architecture

in air traffic control and flight simulation.

Prerequisite

Software engineering



Number Level

CO1 Understand the concepts of software architecture, business cycle and K2

analysis method

CO2 Understand the processes of system development from software K2

architecture

CO3 Apply software design to simple applications K3

CO4 Analyse the software architectures in different domains K4


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Syllabus

UNIT I (11Hrs) Architecture Business Cycle: Introduction - Software processes and the architecture business cycle – Introduction: Software Architecture - Architectural styles, reference models and reference architectures - Importance of software architecture - Architectural structures and views

UNIT II (11Hrs) Creating And Analyzing an Architecture: Quality Attributes: Architectures and Quality Attributes-Architectural Means for Achieving Qualities. Moving from Qualities to Architecture: Architecture Styles: Introducing Architectural Styles – Organizing Architectural Styles – Refinements of Styles – Using Styles in System Design – Achieving Quality Goals with Architectural Styles

UNIT III (11Hrs)

The Software Architecture Analysis Method: The How and Why of Analyzing Software Architecture – Overview of Software Architecture Analysis Method – A Small Example of SAAM Application –

M.ScCS 59

SAAM Applied to a Financial Management System – SAAM Applied to a Revision – Control System – Observations on SAAM. Architecture Reviews: Costs and Benefits - Review Techniques – The Review Practice

UNIT IV (12Hrs) Moving From Architectures to Systems: Architecture Description Languages Today – Capturing

Architectural Information in an ADL – ADLs Help System Development – Choosing an ADL – An Example of an ADL

UNIT V (11 Hrs) Air Traffic Control: A Case Study in Designing for High Availability: Relationship to the Architecture Business Cycle – Requirements and Qualities – Architectural Approach – Architectural

Solution – Assessing the Architecture for Maintainability. Flight Simulation: A Case Study in

Architecture for Integrability: Relationship to the Architecture Business Cycle – Requirements and Qualities – Architectural Approach – Architectural Solution

Text Book Len Bass, Paul Clements, Rick Kazman (2013). Software Architecture in Practise, 3/e, Pearson Education.

Reference Books 1. Mary Shaw David Garlan (2007). Software Architectural Perspectives on an emerging discipline,

Prentice Hall of India 2. Muhammad Ali Babar, Alan W. Brown, Ivan Mistrik (2014). Agile Software Architecture:

Aligning Agile Processes and Software Architectures; Elsevier Inc. 3. Frank Buschmann, Regine Meunier, Hans Rohnert, Peter Sommerlad, Michael Stal (2001).

Pattern-Oriented Software Architecture, A system Patterns, John Wiley and Sons.

Pedagogy

Lectures, Case studies, Group Discussions

Course Designers: 1. Mrs.T.Thendral 2. Mrs.V.Santhana Lakshmi

M.ScCS 60

RS17E06 SOFT COMPUTING Category L T P Credit

III 56 4 - 4

Preamble This course covers the concepts of neural networks and the role of neural networks in intelligent

systems. It also presents fuzzy set theory, fuzzy logic, genetic algorithm, and hybrid system.

Prerequisite Artificial Intelligence



Number Level

CO1. Understand the concepts of soft computing and their applications K2

CO2. Summarize supervised and unsupervised learning in neural networks K2

CO3. Apply soft computing techniques for small applications K3

CO4. Analyze various soft computing techniques suitable for real time K4

applications

CO5. Evaluate the results of knowledge base system K5


Cos PO1 PO2 PO3 PO4

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Syllabus

UNIT I (11 Hrs)

Neural Networks : Fundamentals of Neural Networks – Basic Concepts of Neural Networks – Model

of an Artificial Neuron – Neural Network Architecture – Characteristics of Neural Network –

Learning Methods – Taxonomy of Neural Network Architecture – Back Propagation Network –

Architecture of Back Propagation Network – Back Propagation Learning

UNIT II (12 Hrs) Neural Network Associative Memory: Auto Correlations – Hetero Correlations – Exponential BAM

– Associative Memory for Real Coded Pattern Pairs – Adaptive Resonance Theory – Introduction –

ART1 – ART 2 - Applications

M.ScCS 61

UNIT III (11 Hrs)

Fuzzy Set Theory: Crisp Sets – Fuzzy Sets – Crisp Relations – Fuzzy Relations – Fuzzy Systems:

Crisp Logic – Predicate Logic – Fuzzy Logic – Fuzzy Rule Based System – Defuzzification Method

- Applications

UNIT IV

(11Hrs)

Genetic Algorithms: History – Basic Concepts – Creation of off Springs – Working Principle –

Encoding – Fitness Function – Reproduction .Genetic Modeling – Inheritance Operators – Cross

Over – Inversion and Deletion – Mutation Operator –Applications – Advances in Genetic Algorithm

UNIT V (11Hrs)

Hybrid System: Integration of Neural Network – Fuzzy Logic – Genetic Algorithm-Hybrid System –

Neural Network – Fuzzy Logic – Genetic Algorithm Weight Determination – Application – Fuzzy

Back Propagation Network – Language Recognition Type Fuzzy Members – Fuzzy Neuron – Fuzzy

Back Propagation Architecture – Learning in Fuzzy Back Propagation – Applications – Knowledge

Base Evaluation

Text Book S.Rajasekaran and G.A.Vijayalakshmi Pai (2011).Neural Networks,Fuzzy Logic and Genetic Algorithms Synthesis and Application, Prentice Hall of India,Pvt. Ltd.

Reference Books 1. Vinoth Kumar and R. Saravana Kumar (2012). Neural Network and Fuzzy logic, S.K. Katria & Sons 2. Haykin Simon (2011).Neural Networks and Learning Machines, 3/e, Prentice Hall of India 3. Tang,Tan and Yi (2010).Neural Networks: Computational Models and Application,

Springer Verlag Publications

Pedagogy: Lectures, Demonstrations, Group Discussions

Course Designers

1. Mrs.V.Kalaimani


M.ScCS 62

RB17E07 /

MIT1709 BIG DATA ANALYTICS Category L T P Credit

III 56 4 - 4

Preamble This course gives an introduction tobig data tools, techniques, storage and Hadoop ecosystem. It also presents the concepts of MapReduce and data management in NoSQL and R programming

Prerequisite

Database Management systems Data mining



Number Level

CO1. Understand the characteristics of big data, tools, techniques, storage and K2

Hadoop ecosystem

CO2.

Understand data management concepts in NoSQL databases and R

programming K2

CO3. Apply Mapreduce concepts to process big data K3

CO4. Analyze Hadoop components and their uses for big data processing K4

CO5.

Design programs for big data applications using Hadoop components and R programming K4


COs PO1 PO2 PO3 PO4

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CO2. S M M M

CO3. S S M M

CO4. S M S M

CO5. S S S M


Syllabus

UNIT I (11 Hrs) Introduction –Big Data - Characteristics of Big Data- Structure of Big Data- Risk of Big Data-

Exploring Big Data-Big Data Business model- Big Data Technologies-Web Data Overview – Web

Data in Action.

UNIT II (11 Hrs) Hadoop: Introduction–Comparison with other systems- History of Hadoop - Apache Hadoop andHadoop Ecosystem - Mapreduce – introduction-Analyzing the data with Hadoop- -Hadoop

Distributed File System- Design – concepts-Anatomy of a MapReduce Job Run – Classic –

Mapreduce features- counters-sorting

M.ScCS 63

UNIT III (11 Hrs) Hadoop Components: Pig–Introduction–Comparison with databases-Pig Latin- Data

processingoperators – Hive – Comparison with traditional databases-HiveQL - tables- Hbase - introduction-concepts - Hbase versus RDBMS

UNIT IV (12 Hrs) NoSQL: Introduction to NoSQL- Key-value stores-Document databases-Graph databases Storagearchitecture: Working with column oriented databases- Document store internals- Understanding key value stores-Indexing in MongoDB

UNIT V (11 Hrs) R Basics:- Introduction- Packages and Library – Data types – Basic operators – R objects- Vectors –

Lists- Arrays – Matrix- Factors – Data frame- R file formats- Importing and exporting files – Data

Visualization in R: Lattice package- Box plot- bar chart – scatter plot- GGplot2

Reference Books 1. Bill Franks (2012). Taming the Big Data Tidal wave, John Wiley & Sons 2. Tom White (2012). Hadoop : The Definitive Guide, Third Edition,O’Reilly Media

3. Shashank Tiwari (2011). Professional NoSQL, John Wiley & Sons 4. V. Bhuvaneswari (2016). Data Analytics with R, Bharathiar University.

Pedagogy: Lectures, Demonstrations, Group discussions

Course Designers: 1. Mrs.V. Preamsudha

2. Mrs.R.Kowsalya

M.ScCS 64

RI17E08 INFORMATION RETRIEVAL Category L T P Credit

III 56 4 - 4

Preamble This course presents the concepts of document representation, document indexing, digital information storage, retrieval and distribution. It also introduces effective search strategies for IR systems, vector space model, text classification and evaluation methods of IR systems.

Prerequisite

Database Management systems Data mining

Course Outcomes On the successful completion of the course, students will be able to


Number Level

CO1. Understand the concepts of document representation, document indexing, K2

digital information storage, retrieval and distribution

CO2. Summarize the advantages and disadvantages of different information- K2

retrieval design models

CO3. Demonstrate document classification applying the concepts of vector spaces K3

and classifiers

CO4. Analyze the effective search strategies for IR systems K4

CO5. Assess the result of an information retrieval system K5


COs PO1 PO2 PO3 PO4

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Syllabus

UNIT I (11Hrs) Boolean retrieval: Information retrieval problem - Processing Boolean queries - Boolean model versus ranked retrieval. The term vocabulary and postings lists: Document delineation and character

sequence decoding - Determining the vocabulary of terms - Faster postings list intersection via skip

pointers - Positional postings and phrase queries

M.ScCS 65

UNIT II (12Hrs) Dictionaries and tolerant retrieval: Search structures for dictionaries - Wildcard queries - Spelling

correction - Phonetic correction. Index construction: Hardware basics - Blocked sort-based indexing

- Single-pass in-memory indexing - Distributed indexing - Dynamic indexing - Other types of indexes

UNIT III (11Hrs) Scoring, term weighting and the vector space model: Parametric and zone indexes - Term frequency and weighting - The vector space model for scoring. Evaluation in information retrieval:

Information retrieval system evaluation - Standard test collections - Evaluation of unranked

retrieval sets - Evaluation of ranked retrieval results – Assessing relevance

UNIT IV (11Hrs)

XML retrieval: Basic XML concepts - A vector space model for XML retrieval - Evaluation of XML retrieval - Text-centric vs. data-centric XML retrieval. Text classification and Naive Bayes:

The text classification problem - Naive Bayes text classification - Properties of Naive Bayes - Feature selection - Evaluation of text classification

UNIT V (11Hrs) Vector space classification: Document representations and measures of relatedness in vector spaces - Rocchio classification - k nearest neighbor - Linear versus nonlinear classifiers - Flat clustering:

Clustering in information retrieval - Problem statement - Evaluation of clustering - K-means - Cluster cardinality in K-means

Text Book Christopher D. Manning, Prabhakar Raghavan, Henrich Schutze (2008). Introduction to Information Retrieval, 1/e; New York: Cambridge University Press

Reference Books 1. Stefan Buttcher et.al (2012). Information Retrieval - Implementing and Evaluating, MIT Press 2. Dr Ricardo Baeza-Yates et.al (2011). Modern Information Retrieval: The Concepts and

Technology, Addison Wesley 3. David A. Grossman and Ophir Frieder (2010). Information Retrieval,2/e, Universities Press

Pedagogy: Lectures, Demonstrations, Guest Lecture, Video Lectures

Course Designers


2. Dr. M. S. Vijaya

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Stefan+Buttcher&search-alias=stripbooks

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Dr+Ricardo+Baeza-Yates&search-alias=stripbooks

M.ScCS 66

RV17E09 VIRTUAL REALITY


III 56 4 - 4

Preamble This course provides the technology behind virtual reality and introduces input, output devices used for virtual reality. It also presents the techniques and applications used for augmented reality.

Prerequisite.

Animation Techniques Image Processing


CO CO Statement Knowledge Number Level

CO1. Understand the basic concepts of virtual reality K2

CO2. Understand the fundamental principles of augmented reality. K2

CO3.

Apply appropriate techniques and design augmented reality applications K3

CO4. Analyze the techniques required for virtual reality environments K4

CO5.

Assess the methods and techniques appropriate for virtual reality applications K5


Cos PO1 PO2 PO3 PO4

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CO2. M M M M

CO3. M M M M

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Syllabus

UNIT I (11 Hrs)

Introduction: The Three Fs of Virtual Reality - A Short History of Early Virtual Reality – Early

Commercial VR Technology - VR Becomes an Industry - The Five Classic Components of a VR

System UNIT II (12 Hrs) Input Devices : Three – Dimensional Position trackers – Tracker Performance Parameters –

Mechanical Trackers – Magnetic Trackers – Ultrasonic Trackers – Optical Trackers – Hybrid Inertial

Trackers - Navigation and Manipulation Interfaces - Tracker-Based Navigation Manipulation

Interfaces – Trackballs - Three-Dimensional Probes - Gesture Interfaces - The Pinch Glove - The

5DT Data Glove - The Didjiglove - The CyberGlove

M.ScCS 67

UNIT III (11 Hrs)

Output Devices: Graphics Displays: The Human Visual System - Personal Graphics Displays -Large-Volume Displays - Sound Displays - The Human Auditory System - The Convolvotron – Speaker Based Three-Dimensional Sound - Haptic Feedback : The Human Haptic System - Tactile Feedback Interfaces - Force Feedback Interfaces

UNIT IV (11 Hrs)

Introduction to Augmented Reality - Definition – Examples – Displays - Visual perception -Requirements and characteristics – Tracking - Characteristics of tracking technology - Stationary tracking systems - Mobile sensors

UNIT V (11 Hrs)

Computer Vision for Augmented Reality - Natural feature tracking by detection – Simultaneous

localization and mapping – Interaction - Output modalities – Input modalities – Tangible interfaces –Navigation

Text Book 1. Grigore C. Burdea, Philippe Coiffet (2010),Virtual Reality Technology, 2/e, Wiley Dream Tech

India

2. Dieter Schmalstieg, Tobias Hollerer (2016), Augmented Reality : Principles and Practice,

Pearson education Inc

Reference Books 1. Jonathan Linowes , Krystian Babilinski (2017), Augmented reality for developers, 1/ e, Packt

Publishing

2. William R. Sherman, Alan B. Craig (2013), Understanding Virtual Reality: Interface,

Application and Design, Morgan Kaufmann Publishers

3. Philippe Fuchs and Guillaume Moreau (2012),Virtual Reality: Concepts and Technologies, CRC

Press

4. Ted Simpson (2011),Virtual Machines, Cengage Learning

Pedagogy: Lectures, Group Discussions, Demonstrations

Course Designers: 1. Mrs. V. Preamsudha

2. Mrs. R. Kowsalya

M.ScCS 68

RG17E10 GRID COMPUTING Category L T P Credit

III 56 4 - 4

Preamble This course contains the basics of Grid Computing introduction, initiatives and applications. This will also offer the technologies involved in grid computing. It also covers the concepts of grid computing toolkits.

Prerequisite

Computer System Architecture Concepts of distributed computing



Number Level

CO1. Understand the concepts of grid computing, grid computing Initiatives and K2

applications

CO2. Understand the technologies like Open Grid Service Architecture and Open K2

Grid Service Infrastructure

CO3. Apply grid computing in different applications K3

CO4. Analyse the architecture of OGSA and OGSI technology in grid computing K4

CO5. Analyse the standard projects in Grid Computing K4


Cos PO1 PO2 PO3 PO4

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CO2. S S S M

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Syllabus

UNIT I (11 Hrs) Grid Computing: Introduction-Early Grid Activities-Current Grid Activities-An Overview of Grid Business Areas-Grid Applications-Grid Infrastructure

M.ScCS 69

UNIT II (12 Hrs)

Grid Computing Initiatives: Grid Computing Organizations and their roles – Grid Computing

analog– Grid Computing Road map

UNIT III (11 Hrs) Grid Computing Applications: Merging the Grid Sources – Architecture with the Web Devices Architecture

UNIT IV (11 Hrs) Technologies: OGSA – Sample use cases – OGSA platform components – OGSI – OGSA Basic services

UNIT V (11 Hrs) Grid Computing Toolkits: GLOBUS GT3 Toolkit: Architecture – GT3 Software Architecture Model. GLOBUS GT3 Toolkit: Programming Model – Grid Service Behavior Implementation

– Factory Callback Mechanism – Grid Service Lifecycle Callbacks and Lifecycle Management

– Grid Service Lifecycle Model – GT3 Tools

Text Book Joshy Joseph & Craig Fellenstein (2004). Grid Computing, Pearson Education

Reference Books 1. Ahmar Abbas (2003). Grid Computing: A Practical Guide to Technology and

Applications,Charles River Media, New Delhi 2. Radu Prodan Thomas Fahringer (2007). Grid Computing: Experiment Management, Tool

Integration, And Scientific Workflows, Prism Books Pvt Ltd 3. Prabhu C.S.R. (2008) . Grid And Cluster Computing, PHI Learning Pvt. Ltd 4. Fran Berman, Barry Wilkinson (2009). Grid Computing: Techniques and Applications,

CRC Press

Pedagogy: Lectures, Discussions, Case Study

Course Designers: 1. Mrs.T.Thendral 2. Mrs.R.Kowsalya

psgr krishnammal college for women college of … · summer internship students will undergo summer...

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