Syllabus for
Master of Science (Computer Science and Applications)
Academic Year  (2023)

MSc Computer Science and Applications is a 4-semester programme offered for the professionals working in the software industry or related fields. This program is intended to enhance student’s academic foundations with comprehensive understanding of advance tools and technologies. The objective of the course is to mould students to acquire analytical, creative and problem-solving skills to meet the industry standards. Enlighten students with the research processes and activities to meet future challenges. The progremme offers courses like neural networks, machine learning, IoT, blockchain etc., to meet current trends in industries.

Programme Outcome/Programme Learning Goals/Programme Learning Outcome:

PO2: Identify the need and scope of Interdisciplinary research

PO3: Enhance research culture and uphold the scientific integrity and objectivity

PO4: Understand the professional, ethical and social responsibilities

PO5: Understand the importance and the judicious use of technology for the sustainability of the environment

PO6: Demonstrate disciplinary competency, employability and leadership skills

Programme Specific Outcome:

PSO2: Project Management and Professional Ethics: Apply standard practices in software project development

PSO3: Conduct Investigation of Complex Computing Problems: Understand, analyze and develop computer-based systems of varying complexity

PSO4: Computer Science Research and Development: Develop computer science research competence for high profile career opportunities

PSO5: Modern Tool Usage: Apply their knowledge and experience on modern computing tools and platforms for continuing professional development

PSO6: Innovation and Entrepreneurship: Produce innovative IT products and services based on global needs and trends

Programme Educational Objective:

1.      Evaluation Pattern: 60% CIA + 40% ESE

2.      Tutorials / Assignments / Tests / Quiz / Seminar.

3.      Attendance is part of the CIA component.

4.      Minimum percentage to pass in each paper is 50% (CIA + ESE).

To introduce the concepts and principles of Java Programming language and to design and implement object-oriented solutions to simple and complex problems. To experience in java programming within an integrated development environment

Review of the fundamentals of Java Programming - Class and Objects - Inheritance in Java - Inheritance in classes - Using super - Method overriding - Dynamic Method Dispatch - Abstract Classes - Using final with inheritance - the Object Class - Interfaces and Packages - Inheritance in java with Interfaces  - Defining Interfaces - Implementing Interfaces - Extending Interfaces - Creating Packages - CLASSPATH variable - Access protection - Importing Packages - Interfaces in a Package - Exception Handling in Java - try-catch-finally mechanism - throw statement - throws statement - Classes for Exception Handling

Input / Output in java - java.io package - I/O Streams - Readers and Writers - Using various I/O classes – Reader, Writer, Input Stream and Output Stream - Serialization of objects Multithreading - Life cycle of a thread - Java Thread priorities - Runnable interface and Thread Class - Sharing limited Resources - Shared Object with Synchronization – Comparators – Collections - Collection-classes – List – Set – Maps – Trees - Iterators

GUI  concepts  in  java -  Basic  GUI  Components  in  AWT -  Container  Classes -  Layout Managers - Flow Layout - Border Layout-Card Layout - Box Layout - Difference between AWT and SWING - Event Handling-Handling Keyboard Events and Mouse Events - Handling Sessions and Cookies - Servlet Model – Overview -  Environment Setup - Life Cycle -  Examples - Client Request - Server Response

Networking - Creating a server that sends data - Creating a client that receives data - two way communications between server and client - Difference between Server Socket and Socket – RMI - JDBC - Using MS-Sql Server Stages in a JDBC program - Registering the driver - Connecting to database - Transaction and Non-Transactional Events - Preparing SQL statements - various methods of statements and differences - Improving the performance of a JDBC program

Java Server Pages - The Problem with Servlets - Life Cycle of JSP Page - JSP Processing - JSP Application Design with MVC - Setting Up the JSP - Environment - JSP Directives - JSP Action - JSP Implicit Objects - JSP Form Processing - JSP Session and Cookies Handling - JSP Session. Tracking - JSP Database Access - JSP Standard Tag Libraries - JSP Custom Tag - JSP Expression Language - JSP Exception Handling - JSP XML Processing

[2].     Kathy walrath,“ Java server programming J2EE”, 1st ed.,Black Book, Dream Tech Publishers, , 2015

[2].     RaoNageswara, “Core Java: An Integrated Approach”, Dreamtech press, 2nd Edition, 2010.

[3].     James Keogh, “Complete Reference J2EE”McGraw publication, 2015.

To enable the students to learn the basic functions, principles and fundamental aspects of computer architecture and design in terms of digital logic elements and circuits, central processing unit and memory unit.

Number system- Decimal number system- Binary number system - octal number system - hexadecimal number system - number system conversion - number representation - unsigned representation – signed number representation - 1’s complement – 2’s complement- 9’s complement – 10’s complement - binary arithmetic operation- binary addition- binary subtraction - Binary multiplication - binary division - Binary codes - weighted codes and unweighted codes

Introduction - Boolean algebra - Boolean operators - truth table - laws of Boolean algebra - De Morgan’s Law - Logic gates - Description of logic gates - Universal properties - Simplification of logic functions - Simplification using NAND and NOR  gate - logic expression - minterm – maxterm - SOP - POS expression - minimization techniques - Karnaugh Map

Self learning: Implementation using simulator

Digital circuits - Combinational circuits - Half Adder – Full adder - Half subtractor - Full subtractor – Encoder – Decoder - BCD to seven segment display – Multiplexer - Demultiplexer

Sequential circuits – Latches – SR-Latch - Flip Flop - SR flip flop - D flip flop - JK flip flop- master slave JK FF - Timing diagrams – Registers - Shift Register - SISO – SIPO – PISO – PIPO – Counters - Synchronous counters - Asynchronous counters - Decade counter - Mod counters- Timing diagrams

Basic Structure of Computers: Basic Operational Concepts - Bus Structures – Processor Clock - Clock Rate - Instruction set: CICS and RISC.

Basic Processing Unit: Some Fundamental Concepts - Multiple Bus Organization - Hard-wired Control - Micro programmed Control.

The memory system: Semiconductor RAM memories - Internal organization of memory chips - static memories – ROM - Cache memories

[2]. V.Carl Hamacher, Zvonko G. Varanesic and Safat G. Zaky, Computer Organisation, 6th edition, Mc Graw-Hill Inc, 2013.

[2] Bartee, Thomas C, Digital Computer Fundamentals, Tata Mc Graw-Hill, 6th edition, 2013.

[3] William Stallings, Computer Architecture and Organization, PHI, Eigth Edition, 2015.

[4] David A. Patterson and John L.Hennessey, Computer Organization and Design, Morgan Kauffman / Elsevier, Fifth edition, 2014.

This course concentrates on introduction, principles, design and implementation of advanced database concepts. Objective of the course is to provide strong foundation of database concepts and develop skills for the design,   storage and retrieval in relational databases, XML and NoSQL databases.

Database system applications - Purpose of database systems - View of data - Data models - Database languages - Database storage and querying - Transaction management - Database architecture - Database users and administrators

Structure of relational databases - Database schema - Keys, Schema diagrams, Design process - ER model – Constraints - ER diagrams - Aspects of database design - atomic domains and 1NF - Decomposition using functional dependencies - Functional dependency theory

File organization - Organization of records in files - Data dictionary storage - Basic indexing concepts - Ordered indexes - B+ tree index - Static hashing - Dynamic hashing - Bitmap index

Motivation - Structure of XML Data - XML Document Schema - Querying and Transformation - Application Program Interfaces to XML - Storage of XML Data - XML Applications.

Definition and introduction - Document databases – MongoDB - Storing data and accessing data from MongoDB - Querying MongoDB - Document store internals - MongoDB reliability and durability - Horizontal scaling - CRUD operations in MongoDB - Creating and using indexes in MongoDB

[2].     ShashankTiwari, “Professional NoSQL”, John-Wiley, 2011.

[2].     RamezElmasri, ShamkantNavathe, “Fundamentals of Database Systems”, Addison-Wesley, 6th Edition, 2011.

[3].     Kristina Chodorow, “MongoDB: The Definitive Guide”, O'Reilly, 2nd Edition, 2013.

The objective of this course is to provide comprehensive knowledge of Data Analytics using python program development environment.

Structure of Python Program-Underlying mechanism of Module Execution-Branching and Looping-Problem Solving Using Branches and Loops-Functions - Lists and Mutability- Problem Solving Using Lists and Functions

Sequences, Mapping and Sets- Dictionaries- -Classes: Classes and Instances-Inheritance-Exceptional Handling-Introduction to Regular Expressions using “re” module.

Basics of NumPy-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 Data - Hierarchical Indexing - Combining Data Sets - Aggregation and Grouping - Pivot Tables.

Basic functions of matplotlib - Simple Line Plot, Scatter Plot - Density and Contour Plots -Histograms, Binnings and Density - Customizing Plot Legends, Colour Bars - Three-Dimensional Plotting in Matplotlib.

[2] Zhang.Y, An Introduction to Python and Computer Programming, Springer Publications, 2016.

[2] T.R.Padmanabhan, Programming with Python, Springer Publications, 2016.

The course builds the logical thinking in the students with the help of the programming. It also facilitates the students to build applications using java programming. The database concepts help the student to learn advance database connectivity and usage. 

1.     Demonstrate objects and classes (constructor, access specifier, method overloading)

2.     Demonstrate static block, static variables and static methods

3.     Demonstrate inheritance in java

4.     Demonstrate use of super and this

5.     Demonstrate abstract class

6.     Demonstrate interfaces in java

7.     Demonstrate exception handling in java

8.     Demonstrate multithreading in java

9.     Demonstrate applets in java

10.  Demonstrate two way communication between server and client

1. 1.  Select queries and DML
2. PL/SQL
3. Data manipulation with MongoDB

[2].     RaoNageswara, “Core Java: An Integrated Approach”, Dreamtech press, 2nd Edition, 2010.

James Keogh, “Complete Reference J2EE”McGraw publication, 2015.

This course provides a more comprehensive understanding of data structure and algorithm development with practical implantation of the concepts.

Basic Operations – Implementation - Stack applications - Recursion- A Case Study - Queue operations – implementation - Applications of a queue - Linked Lists: Linked list algorithms - Processing a linked list - Linked list algorithms (Create, Traverse, Insert, Delete, Search, Destroy) - doubly linked lists structures and its operations - Applications of linked lists - Algorithmic efficiency in terms of space and timecomplexity

Basic tree concepts - Binary trees - Binary tree traversals - Expression trees - General trees - Changing general tree to binary tree - General tree insertion - Search trees - Binary search trees – Operations – Traversals : BFS and DFS methods - Searching a BST - Algorithms for and traversing and searching - AVL trees - AVL Balance factor - Balancing trees - AVL Insert - AVLDelete

M-Way search trees - B Trees - B-Insertion - B-Tree Deletion - B –Tree Traversal - Tree Search

- Simplified B-Trees - 2-3 Tree - 2-3-4 Tree - B-Tree Variations – B * Trees - B+ Trees.

Terminology – operations - Graph storage structures – Adjacency Matrix - Adjacency lists - Graph algorithms - Create insert vertex - Delete vertex - Retrieve vertex - Depth first traversal and Breadth First Traversal – Networks : Minimum spanning tree - Shortest Pathalgorithm

General sort concepts - O Notation - Sort Algorithms - Quick Sort - Heap sort - Sorting using a Heap - Shell sort - Merge sort - radix sort - merging two sorted lists - Efficiency considerations - comparative study

[2]. A M Tanenbaum, Y Langsam and M. J. Augenstein, “Data Structure using C”, 2nd Edition, Prentice- Hall, India, 2007.

2.      Tutorials / Assignments / Tests / Quiz / Seminar.

This course aims to set the foundation for computer networks and introducing the cryptographic approaches. The course covers the communication process between devices with standard set of protocols based on Internet model (TCP/IP). The last two units presents the cryptographic approaches used in for network security. 

Data Communications- Data Transmission: Concepts and Terminology, Analog and Digital Data Transmission, Transmission Impairments, Channel Capacity; Transmission Media: Guided Transmission Media, Wireless Transmission, Wireless Propagation, Line-of-Sight Transmission; Signal Encoding Techniques: Digital Data, Digital Signals, Digital Data, Analog Signals, Analog Data, Digital Signals, Analog Data, Analog Signals.

Digital Data Communication Techniques- Asynchronous and Synchronous Transmission, Types of Errors, Error Detection, Error Correction, Line Configurations; Multiplexing: Frequency, Division Multiplexing, Synchronous Time-Division Multiplexing, Statistical Time-Division Multiplexing, Asymmetric Digital Subscriber Line, Switched Communications Networks, Circuit Switching Networks, Circuit Switching Concepts, Softswitch Architecture, Packet-Switching Principles.

Congestion Control in Data Networks- Effects of Congestion, Congestion Control, Traffic Management, Congestion Control in Packet-Switching Networks; Cellular Wireless Networks: Principles of Cellular Networks, First Generation Analog, Second Generation CDMA, Third Generation Systems; High-Speed LANs: The Emergence of High-Speed LANs, Ethernet, Fibre Channel; Wireless LANs: IEEE 802.11 Architecture and Services; Internetwork Protocols - Internetwork Protocols: Internet Protocol, IPv6; Transport Protocols: Connection-Oriented Transport Protocol Mechanisms, TCP, TCP Congestion Control, UDP.

Introduction to Cryptography and Data Security - Stream Ciphers -  The Data Encryption Standard (DES) and Alternatives - The Advanced Encryption Standard (AES) - More About Block Ciphers - Introduction to Public-Key Cryptography - The RSA Cryptosystem -  Public-Key Cryptosystems Based on the Discrete Logarithm Problem - Elliptic Curve Cryptosystems

Digital Signatures - The RSA Signature Scheme - The Digital Signature Algorithm (DSA) -  Hash Functions  - Message Authentication Codes (MACs) - Principles of Message Authentication Codes - MACs from Hash Functions: HMAC - Key Establishment.

[2].     Bart Preneel, “Understanding Cryptography”, Springer Heidelberg Dordrecht London New York, 2010.

[2].     AtulKahate, “Cryptography and Network Security”, Tata McGraw-Hills, 2010.

[3].  Brijendra Singh, “Network Security and Management”, PHI, 3rd Edition, 2013.

[4].  William Stallings, “Cryptography and Network Security”, Prentice Hall, 6th Edition, 2014.

ESE (Weightage): 40%

The research writing for Computer Science is intended to assist students in planning and carrying out research projects. The students are exposed to the principles, procedures, and techniques of implementing a research project. The course starts with an introduction to research and carries through the various methodologies involved.

Defining research problem - selecting the problem - necessity of defining the problem - techniques involved in defining a problem- Ethics in Research. Kinds of Publication, Writing, Science, and Skepticism, Shaping a Research Project, Research Planning, Students and Advisors, A “Getting Started” Checklist. Reading and Reviewing: Research Literature, Finding Research Papers, Critical Reading, Developing a Literature Review, Authors, Editors, and Referees, Contribution, Evaluation of Papers, Content of Reviews, Drafting a Review.

Hypotheses, Defending Hypotheses, Forms of Evidence, Use of Evidence, Approaches to Measurement. Writing a Paper: The Scope of a Paper, Organization, Title and Author, Abstract, Introduction, Body, Literature Review, Conclusions, From Draft to Submission, Co-authoring, Thesis. Algorithms: Presentation of Algorithms, Formalisms, Environment of Algorithm. Graphs, Figures, and Tables, Editing: Proofreading, Choice of Word-Processor.

Latex: Introduction, text, tables, figures, equations, citations, referencing, and templates (IEEE style), paper writing for international journals, Writing scientific report: literature review. On-line Searching: Database – SciFinder – Scopus - Science Direct - Searching research articles - Citation Index - Impact Factor - H-index etc.

Persuasive Data, Interpretation, Robustness, Performance of Algorithms, Human Studies, Coding for Experimentation, Describing Experiments.  Statistical Principles: Variables, Samples and Populations, Aggregation and Variability, Reporting of Variability, Statistical Tools, Randomness and Error, Intuition, Visualization of Results.

Research Talks, Content, Organization, The Introduction, The Conclusion, Preparation, Delivery, Slides, Copyright, Posters. Ethics: Intellectual Creations, Plagiarism, Self-plagiarism, Misrepresentation, Authorship, Confidentiality and Conflict of Interest

[2] C. R. Kothari, Research Methodology Methods and Techniques, 3rd. ed. New Delhi: New Age International Publishers, Reprint 2014.

1.C.R. Kothari, Gaurav Garg, “Research Methodology: Methods and Techniques”, New Age International, 4th Edition, 2018.

2.Subbaram N.R. “Handbook of Indian Patent Law and Practice”, S. Viswanathan (Printers and Publishers) Pvt. Ltd., 1998.

3.Ranjit Kumar, “Research Methodology a step-by step guide for beginners”. (For the topic Reviewing the literature under module 2), SAGE Publications Ltd, 3rd Edition, 2011 

4.Intellectual Property Today: Volume 8, No. 5, May 2001, [www.iptoday.com]. 

5.Meredith Zozus, “The Data Book: Collection and Management of Research Data” (Chapman & Hall/CRC , 2017. 

6.Wendy Olsen, “Data Collection Key Debates and Methods in Social Research”, SAGE Publications Ltd, 2011. 

7.Stefan Kottwitz, “LaTeX Beginner's Guide”, Packt publishing, 2011. 

8.Zobel Justin, “Writing for Computer Science”, Springer, 2014. 

9.Thomas Lancaster, “Avoid Plagiarism”, First Edition, SAGE Publications Ltd, 2019. 

10.Ehtiram Raza Khan, Huma Anwar, “Research Methods of Computer Science”, First Edition, UNIVERSITY SCIENCE PRESS (An Imprint of Laxmi Publications Pvt. Ltd.), 2016. 

11.Jonathan Lazar, Jinjuan Heidi Feng, Harry Hochheiser, “Research Methods in Human-Computer Interaction”, 1st Edition, Morgan Kaufmann, 2nd Edition, 2017.

12.Kirsty Williamson and Graeme Johanson (Ed), “Research Methods - Information, Systems, and Contexts”, Second Edition, Elsevier, 2018.

13.Pandian M Vasant, “Handbook of Research on Emergent Applications of Optimization Algorithms”, IGI Global, 2017.

14.Vicente Garca Daz, “Handbook of Research on Innovations in Systems and Software Engineering”, IGI Global,August 2014.

15.Zina O’Leary, The Essential Guide of Doing Research, New Delhi: PHI, 2005.

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 – Planning and Acting in the Real World

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

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

     Pearson Education, 2019.

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

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

2.     Tutorials / Assignments / Tests / Quiz / Seminar.

This course provides different ways to solve business intelligence problems using various data structures and writing programs for these solutions

Pre-Lab: Software Installation and Configuration

1. Create a Relational Data bases

2. Design an ETL System using SSIS

3. Design a dimensional model using SSAS

4. Design reports using SSRS

5. Design a dashboard using power pivot

1. Implementation of insertion, selection and merge sorting Methods

2. Implementation of stacks

3. Implementation of queues

4. Implementation of Linked list

5. Implementation of two way linked list

6. Implementation of circular linked List

7. Implementation of Binary search tree

8. Implementation of radix and heap sort

9. Implementation of DFS for graphs

10. Implementation of BFS for graphs

2. Joy Mundy, Warren Thornthwaite and Ralph Kimball, “The Microsoft Data Warehouse Toolkit: With SQL Server 2008 R2 and the Microsoft Business Intelligence Toolset”, John Wiley & Sons, 2nd edition, 2011.

2.Gert H. N. Laursen and Jesper Thorlund, “Business Analytics for Managers: Taking Business Intelligence beyond Reporting Paperback” , 2013

This course is designed to introduce the students to advanced technologies which can help realization of complex Web applications. Students examine advanced topics in Hyper Text Markup Language, Cascade Style Sheet and JavaScript for interactive web applications that use rich user interfaces and also understand the server-side web technologies for dynamic web applications and creating modern web applications using MEAN and FULL Stack.

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 - 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 Cookies-Introduction to JSON-JSON vs XML-JSON Objects-Importance of Angular JS in web-Angular Expression and Directives-Single Page Application

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

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 - CRUD operation using MongoDB

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

2. Mastering HTML, CSS & Javascript Web Publishing, Laura Lemay, Rafe Colburn & Jennifer Kyrnin, BPB Publications, First edition,2016

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

The course will expose few advanced topics in operating system and concepts related to recent developments in operating system. Objectives of the course are to understand the main concepts of parallel processing systems, distributed systems, real time systems etc., to have an insight into UNIX and MACH operating system and to know the components and management aspects of Real time, Mobile Operating Systems.

General Overview of the System - System Structure – Operating System Services – Introduction to kernel - architecture of unix operating system - introduction to system concepts kernel data structures - The Buffer cache - Buffer Headers – Structure of the buffer pool – Retrieval of a buffer – scenarios for retrieval of a Buffer - Reading and writing disk blocks – Advantages and disadvantages of the buffer cache - Internal Representation of files – Inodes - structure of a regular file - directories - conversion of a path to an inode - Super Block - inode assignment to a New File - Allocation of Disk Blocks - Other file types

UNIX Process Management - The Structure of Processes: Process States and Transitions - Layout of system memory - Context of a process – Sleep – Implementation of System Calls. Process Control - Process Creation – Signals – Process Termination – Invoking other programs – PID & PPID – Changing the size of a process – The shell – System Boot and the init process

Memory Management: Swapping – Demand Paging – A Hybrid System with Swapping and Demand Paging. The I/O Subsystem: Driver Interfaces – Disk Drivers – Terminal Drivers – Streams. Inter Process Communication (IPC): Process Tracing – System V IPC – Network Communications – Sockets. Multiprocessor Systems: Problem with Multiprocessor Systems – Master and Slave processors – Semaphores

Introduction to Distributed system – Remote Procedure Call – Logical clocks – Vector clocks – Distributed mutual exclusion – Non token based algorithms – Token based algorithms – Deadlock algorithms – Election algorithms – Byzantine agreement problem – Load distributing algorithms – Performance comparison. Distributed File system Design – an overview

Real time and Mobile Operating Systems – Basic Model of Real Time Systems – Characteristics – Applications of Real Time Systems – Real time Task Scheduling –Handling resource sharing . Mobile Operating System – Micro Kernel Design – Case study MACH: Introduction to MACH - Process management in MACH-processes-thread scheduling – memory management in MACH-Virtual memory – memory sharing

[2].     Andrew S Tanenbaum, “Distributed Operating Systems”, PHI, reprint 2006.

Rajib Mall, “Real Time Systems: Theory and Practice”, Pearson Education, India, 2006.

[2].     Arnold Robbins, “UNIX in a Nutshell”, In a Nutshell series, 3rd Edition, reprint 2007.

[3].     George Coulouris, Jean Dollimore and Tim Indberg, “Distributed Systems Concepts and Design”, 3rd Edition, Pearson Education, 2002.

Pradeep K Sinha, “Distributed Operating Systems – Concepts and Design”, PHI, 2006.

The goal is to make students familiar with the basic concepts and structure of modern wireless and mobile communication networks.

Wireless Telecommunications Systems and Networks: History and Evolution of Wireless Radio Systems - Development of Modern Telecommunications Infrastructure - Overview of Existing Network Infrastructure - Wireless Network Applications: Wireless Markets

Evolution and Deployment of Cellular Telephone Systems: Different Generations of Wireless Cellular Networks - 1G Cellular Systems - 2G Cellular Systems - 2.5G Cellular Systems - 3G Cellular Systems - 4G Cellular Systems and Beyond - Wireless Standards Organizations

Common Cellular System Components: Common Cellular Network Components - Hardware and Software Views of the Cellular Network - 3G Cellular System Components - Cellular Component Identification - Cell establishment

Wireless Network Architecture and Operation: The Cellular Concept - Cell Fundamentals - Capacity Expansion Techniques - Mobility Management - Wireless Network Security

Introduction to GSM and TDMA - GSM Network and System Architecture - GSM Channel Concept - GSM Identities - GSM System Operations - GSM Infrastructure Communications

CDMA Technology: Introduction to CDMA - CDMA Network and System Architecture - CDMA Channel Concept - CDMA System Operations

CDPD and Edge Data Networks: CDPD – GPRS - GPRS Networks - GPRS Network Details - GPRS Network Layout and Operation - GPRS Packet Data Transfer - GPRS Protocol Reference Model - GPRS Logical Channels - GPRS Physical Channels - GSM/GPRS/Edge Technology

Introduction to wireless LAN 802.11X technologies - Evolution of Wireless LAN - Introduction to IEEE 802.15x Technologies - Wireless PAN Applications and Architecture – Bluetooth -  Introduction to Broadband wireless MAN - 802.16 technologies

[2].     Stallings William, “Wireless Communications and Networks”, Pearson Education Asia, 2nd Edition, 2009.

[3].     Theodore S Rappaport, “Wireless Communications: Principles and Practice”, Pearson Education Asia, 2nd Edition, 2009.

[4].     Jochen Schiller, “Mobile Communication”, Addison-Wesley, 2nd Edition, 2011.

The explosive growth of the “Internet of Things” is changing our world and the rapid growth of IoT components is allowing people to innovate new designs and products at home.  Wireless Sensor Networks form the basis of the Internet of Things. To latch on to the applications in the field of IoT of the recent times, this course provides a deeper understanding of the underlying concepts of IoT and Wireless Sensor Networks.

Introduction to IoT - Definition and Characteristics, Physical Design Things- Protocols, Logical Design- Functional Blocks, Communication Models- Communication APIs- Introduction to measure the physical quantities, IoT Enabling Technologies - Wireless Sensor Networks, Cloud Computing Big Data Analytics, Communication Protocols- Embedded System- IoT Levels and Deployment Templates.

Introduction to Smart Systems using IoT - IoT Design Methodology- IoT Boards (Rasberry Pi, Arduino) and IDE - Case Study: Weather Monitoring- Logical Design using Python, Data types & Data Structures- Control Flow, Functions- Modules- Packages, File Handling - Date/Time Operations, Classes- Python Packages of Interest for IoT.

Home Automation – Smart Cities- Environment, Energy- Retail, Logistics- Agriculture, Industry- Health and Lifestyle- IoT and M2M.

Sensing and Sensors, Wireless Sensor Networks, Challenges and Constraints; Applications:  Structural Health Monitoring, Traffic Control, Health Care; Node Architecture, Operating system

Introduction – Fundamentals of MAC Protocols – MAC protocols for WSN – Sensor MAC Case Study – Routing Challenges and Design Issues – Routing Strategies – Transport Control Protocols – Transport Protocol Design Issues – Performance of Transport Protocols

[2].     KazemSohraby, Daniel Minoli, TaiebZnati ,“Wireless Sensor Networks: Technology. Protocols and Application”, Wiley Publications, 2010 (Unit IV & V)

[3].     WaltenegusDargie, Christian Poellabauer, "Fundamentals of Wireless Sensor Networks: Theory and Practice", A John Wiley and Sons, Ltd., Publication, 2010.

[2].     Michael Miller, “The Internet of Things” , Pearson Education, 2015

[3].     Holger Karl, Andreas Willig, “Protocols and Architectures for Wireless Sensor Networks”, John Wiley & Sons, Inc., 2005.

[4].     ErdalÇayırcı ,ChunmingRong, “Security in Wireless Ad Hoc and Sensor Networks”, John Wiley and Sons, 2009.

[5].     Carlos De MoraisCordeiro, Dharma PrakashAgrawal, “Ad Hoc and Sensor Networks: Theory and Applications (2nd Edition)”, World Scientific Publishing, 2011.

[6].     WaltenegusDargie, Christian Poellabauer, “Fundamentals of Wireless Sensor Networks Theory and Practice”, John Wiley and Sons, 2010

[7].     Adrian Perrig, J. D. Tygar, "Secure Broadcast Communication: In Wired and Wireless Networks", Springer, 2006.

Understand the concept of high performance computing and its applications. The course includes the introduction to load sharing and balancing concepts. The course will discuss Grid computing and cloud computing in terms of their architecture and performance.

Introduction to Cluster Computing, Scalable Parallel Computer Architectures, Cluster Computer and its Architecture, Classifications, Components for Clusters, Cluster Middleware and Single System Image, Resource Management and Scheduling

Programming Environments and Tools, Applications, Representative Cluster Systems, Heterogeneous Clusters, Security, Resource Sharing, Locality, Dependability, Cluster Architectures, Detecting and Masking Faults, Recovering from Faults, Condor, Evolution of Metacomputing.

Load Sharing and Balancing: Evolution, Job and Resource Management Systems, State-of-the-Art in RMS and Job, Rigid Jobs with Process Migration, Communication-Based Scheduling, Batch Scheduling, Fault Tolerance, Scheduling Problem for Network Computing, Dynamic Load Balancing, Mapping and Scheduling, Task Granularity and Partitioning, Static and Dynamic Scheduling.

 Consistent, Inconsistent and Partially-Consistent, QoS Guided Min-Min, Selective Algorithm, Grid Computing Security.

Grid Computing: Introduction to Grid Computing, Virtual Organizations, Architecture, Applications, Computational, Data, Desktop and Enterprise Grids, Data-intensive Applications, High-Performance Commodity Computing, High-Performance Schedulers, 

Immediate and Batch Mode

Connectivity, Resource and Collective Layer, Heterogeneous Computing Systems

Introduction to Cloud Computing, Types: Deployment and Service Models, Characteristics, Applications, Service-Level Agreement, Virtualization, 

Task Computing and Task-based Application Models, Market-Based Management of Clouds, Energy-Efficient and Green Cloud Computing Architecture, Resource Allocation, Leases, 

RR, CLS and CMMS, Workflow Scheduling, Montage, Epigenomics, SIPHT, LIGO, CyberShake, Task Consolidation, Introduction to CloudSim, Cloudlet, VirtualMachine and its Provisioning, Time and Space-shared Provisioning.

[2].      (Edited By) I. Foster and C. Kesselman, “The Grid: Blueprint for a New Computing Infrastructure”, Morgan Kaufmann, Elsevier, 2004.

[3].      D. Janakiram, “Grid Computing”, Tata McGraw-Hill, 2005.

[4].      R. Buyya, C. Vecchiola and S. T. Selvi, “Mastering Cloud Computing Foundations and Applications Programming”, Morgan Kaufmann, Elsevier, 2013.

[2].      B. Wilkinson, “Grid Computing: Techniques and Applications”, CRC Press, 2009.

[3].      C. S. R. Prabhu, “Grid and Cluster Computing”, PHI, 2008.

[4].      B. Sosinsky, “Cloud Computing Bible”, Wiley, 2011.

ESE (Weightage): 40%

To present the main characteristics of distributed systems, as well as the related problems and the most common solutions. Student can implement a simple distributed application using a message based protocol.

Distributed System, Examples of Distributed Systems, Important Issues in Distributed Systems, Implementing a Distributed System, Parallel versus Distributed Systems.

Inter process Communication: Introduction, Processes and Threads, Client–Server Model, Middleware, Network Protocols, Ethernet, Wireless Networks, OSI Model, IP, Transport Layer Protocols, Inter process Communication Using Sockets

The Client-Server Model – (Client and Servers, Addressing, Block versus Nonblocking Primitives, Buffered versus Unreliable Primitives) – Remote Procedure Call – (Basic RPC Operation, Parameter Passing, Dynamic Binding, RPC Semantics in the Presence of Failures) Distributed objects and remote invocation. Models for Communication: Need for a Model, Message-Passing Model for Inter process Communication, Process Actions, and Synchronous versus Asynchronous Systems.

Introduction -- Clock Synchronization – (Logical Clocks, Physical Clocks, Clock Synchronization Algorithms) – Election Algorithms – (The Bully Algorithm, A Ring Algorithm) – Atomic Transactions – (Introduction to Atomic Transactions, The Transaction Model. Implementation, Concurrency Control) – Deadlocks in Distributed Systems – (Distributed Deadlock Detection & Prevention).Resource Deadlock and Communication Deadlock, Detection of Resource Deadlock, Detection of Communication Deadlock

Introduction, Solutions on Message-Passing Systems, Lamport’s Solution, Ricart–Agrawala’s Solution, Maekawa’s Solution, Token-Passing Algorithms, Suzuki–Kasami Algorithm, Raymond’s Algorithm’ - Distributed Snapshot: Introduction, Properties of Consistent Snapshots, Cuts and Consistent Cuts, Chandy–Lamport Algorithm.Global State Collection: Introduction, Elementary Algorithm for All-to-All Broadcasting, Termination-Detection Algorithms, Dijkstra–Scholten Algorithm.

Fault-Tolerant Systems: Introduction, Classification of Faults, Specification of Faults, Fault-Tolerant Systems, Masking Tolerance, Non-masking Tolerance, Fail-Safe Tolerance, Graceful Degradation, Detection of Failures in Synchronous Systems, Tolerating Crash Failures. Distributed File Systems: Introduction – Distributed File System Design – (The File Service Interface, The Directory Server Interface, Semantics of File Sharing) -- Distributed File System Implementation – (File Usage, System Structure, Caching, Replication, An Example: Sun’s Network File System).Distributed Shared Memory: Introduction, What is Shared Memory, Consistency Models, Page-Based Distributed Shared Memory.

[2].     Coulouris G., Dollimore J., Kindberg T. and Blair G., “Distributed Systems: Concepts and Design, Addison-Wesley”, 5th Edition, 2011

[2].     SinghalMukesh, Shivaratri G Niranjan, “Advanced Concepts In Operating Systems Distributed Data Base, And Multiprocessor Operating Systems”, McGraw-Hill, Inc., 2009.

This course provides a broad and in-depth knowledge of Storage and Storage networking concepts, applications, and technologies. Storage Fundamentals including storage attachment architectures, the SCSI protocol, disk and tape drive concepts, RAID and JBOD, IP-based SANs, and Storage Networking Issues. 

Management, Storage System Environment: Information Storage, Evolution of Storage Technology and Architecture, Data Center Infrastructure, Key Challenges in Managing Information, Information Lifecycle Components of Storage System Environment, Disk Drive Components, Disk Drive Performance, Fundamental Laws Governing Disk Performance, Logical Components of the Host, Application Requirements and Disk Performance.

Data Protection, Intelligent Storage system: Implementation of RAID, RAID Array Components, RAID Levels, RAID Comparison, RAID, Impact on Disk Performance, Hot Spares Components of an Intelligent Storage System, Intelligent Storage Array

Types of DAS, DAS Benefits and Limitations, Disk Drive Interfaces, Introduction to Parallel SCSI, Overview of Fibre Channel, The SAN and Its Evolution, Components of SAN, FC Connectivity, Fibre Channel Ports, Fibre Channel Architecture, Zoning, Fibre Channel Login  Types, FC Topologies

General – Purpose Service vs. NAS Devices, Benefits of NAS, NAS File I / O, Components ofNAS, NAS Implementations, NAS File-Sharing Protocols, NAS I/O Operations, FactorsAffecting NAS Performance and Availability.iSCSI, FCIP.Content-Addressed Storage, Storage Virtualization: Fixed Content and Archives, Types of Archive, Features and Benefits of CAS, CASArchitecture, Object Storage and Retrieval in CAS, CAS Examples. Forms of Virtualization,SNIA Storage Virtualization Taxonomy, Storage Virtualizations Configurations, StorageVirtualization Challenges, Types of Storage Virtualization.

Information Availability, BC Terminology, BC Planning Lifecycle, Failure Analysis, BusinessImpact Analysis, BC Technology Solutions. Backup Purpose, Backup Considerations, BackupGranularity, Recovery Considerations, Backup Methods, Backup Process, Backup and restoreOperations, Backup Topologies, Backup in NAS Environments, Backup Technologies.Securing the Storage Infrastructure, Managing the Storage Infrastructure: Storage Security Framework, Risk Triad, Storage Security Domains, Security Implementationsin Storage Networking Monitoring the Storage Infrastructure, Storage Management Activities,Storage Infrastructure Management Challenges, Developing an Ideal Solution.

[2].     Rebert Spalding,“Storage Networks”, The Complete Reference, Tata McGraw Hill,2003.

[3].     Richard Barker and Paul Massiglia: Storage Area Networks Essentials A CompleteGuide to Understanding and Implementing SANs, Wiley India, 2002.

Blockchain is an emerging technology platform for developing decentralized applications and data storage, over and beyond its role as the technology underlying the cryptocurrencies. This course serves as an introduction to the exciting new world of blockchain technologies. It explains in detail how bitcoins are generated/mined, how transactions are being made and how the blockchain makes it possible to keep everything secure, fast and reliable without depending in any trusted party or a financial institution. Limitations of Bitcoin and new cryptocurrency systems will be explored.

Blockchain evolution – Blockchain structure – Blockchain characteristics – Blockchain applications example: Escrow – Blockchain Stack – Domain specific blockchain applications.

Cryptographic hash functions – Hash pointer and data structures – Digital signatures – Public keys as identities – A simple cryptocurrency – Distributed consensus – Consensus without identity using a block chain.

Bitcoin transactions – Bitcoin scripts – Applications of Bitcoin scripts – Bitcoin blocks – Bitcoin network – Simple local storage – Hot and cold storage – Splitting and sharing keys – Online wallets and exchanges – Payment services – Transaction fees – Currency exchange markets.

Task of bitcoin miners – Mining hardware – Mining pools – Mining incentives and strategies – Bitcoin anonymity – Deanonymizing bitcoin – Mixing – Zerocoin and zerocash

History and motivation – Few altcoins in detail – Relationship between bitcoin and altcoins – Merge mining – Atomic cross-chain swaps – Bitcoin backed altcoins – Ethereum and smart contracts.

2. Bitcoin and cryptocurrency technologies: a comprehensive introduction. Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, and Steven Goldfeder. Princeton University Press, First edition, 2016.

2. Blockchain: Blueprint for the new economy. Melanie Swan. O’Reilly. First edition. 2015.

To acquire basic knowledge in machine learning techniques and learn to apply the techniques in the area of pattern recognition and data analytics

Machine Learning - types of machine learning examples - Supervised Learning: Learning class from examples - VC dimension - PAC learning – noise - learning multiple classes – regression - model selection and generalization - dimensions of a supervised learning algorithm - Parametric Methods: Introduction - maximum likelihood estimation - evaluating estimator - Bayes’ estimator - parametric classification

Introduction - subset selection - principal component analysis - factor analysis - multidimensional scaling - linear discriminant analysis - Clustering: Introduction - mixture densities - k-means clustering - expectation-maximization algorithm - hierarchical clustering - choosing the number of clusters - Non-parametric: Introduction - non-parametric density estimation - non-parametric classification

Introduction, univariate trees, pruning, rule extraction from trees, learning rules from data. Multilayer perceptron: Introduction, training a perceptron, learning Boolean functions, multilayer perceptron, backpropogation algorithm, training procedures

Introduction, optical separating hyperplane, v-SVM, kernel tricks, vertical kernel, defining kernel, multiclass kernel machines, one-class kernel machines. Bayesian Estimation: Introduction, estimating the parameter of a distribution, Bayesian estimation, Gaussian processes. Hidden Markov Models: Introduction, discrete Markov processes, hidden Markov models, basic problems of HMM, evaluation problem, finding the state sequence, learning model parameters, continuous observations, HMM with inputs, model selection with HMM.

Introduction, canonical cases for conditional independence, d-separation, Belief propagation, undirected graph: Markov random field. Reinforcement Learning: Introduction, single state case, elements of reinforcement learning, temporal difference learning, generalization, partially observed state.

 Self Learning: Clustering - Decision tree

Service Learning: Introduction to machine learning applications developed for betterment of society through select case studies.

[2].     P. Harrington, “Machine Learning in Action”, Manning Publications, 2012

[3].     C. M. Bishop, “Pattern Recognition and Machine Learning”,  Springer, 2011.

[4].     S. Marsland, “Machine Learning: An Algorithmic Perspective”, 1st Ed. Chapman and Hall, 2009.

[5].     T. Mitchell, “Machine Learning”, McGraw-Hill, 1997

Business intelligence (BI) is a broad category of application programs and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications support the activities of decision support, query and reporting, online analytical processing (OLAP) and analysis.

Defining Business Requirements: Introduction, Uncovering Business Value, Prioritizing the Business Requirements. Designing the Business Process Dimensional Model: Concepts and Terminology, Additional Design Concepts and Techniques. The Toolset: Microsoft DW/BI Toolset, Architecture and Overview of the Toolset.

Creating the Relational Data Warehouse: Getting started, completing the physical design, Define storage and create constraints and supporting objects.

Master Data Services: Managing Master Reference Data, Introducing SQL Server MDS, Creating a Simple Application.

Design and Develop the ETL System: Developing the ETL Plan, Introducing SQL Server Integration Services, Extracting Data, Cleaning and Confirming Data, Delivering Data for Presentation.

Core Analysis Services OLAP Database: Overview, Design the OLAP structure-Planning, getting started, Data source view, Dimension design, Editing dimension, Editing Cube, Physical Design Consideration.

Building the BI Applications in Reporting Services: Overview, High Level Architecture for Reporting, System Design and Development Process, Building and Delivering Reports, Reporting Options.

Power Pivot and Excel: Using Excel for Analysis and Reporting, Architecture, Creating and using Power Pivot Databases, Power pivot Monitoring and Management.

Case study: Any Two Applications (eg. Healthcare, Retail Industry)

[2]. Mike Biere,“Business Intelligence for the Enterprise” , second edition, 2009

To provide fundamental concepts of risk analysis and relevant details related to types of risks, risk management strategies and tools used for risk analysis.

Definition -Understanding Risk- Nature of Risk, Source of Risk, Need for risk, management, Benefits of Risk Management, Risk Management approaches.

Credit risk, market risk, operational risk and other risk, Risk Measurements -Measurement of Risk – credit risk measurement, market risk, measurement, interest rate risk measurement, Asset liability management, measurement of operational risk

Risk management- Managing credit risk, managing operational risk, managing market risk, insurance

Derivatives, combinations of derivative instruments, Neutral and volatile strategies, credit derivatives, credit ratings, swaps.

Issues in risk management – Regulatory framework, Basel committee, legal issues, accounting issues, tax issues, MIS and reporting, integrated risk management

[2]. AswathDamodharan,“Strategic Risk Taking”, Pearson, 2008.

The main objective of the courseis aimed at an entry level study of information retrieval and web mining techniques. It is about how to find relevant information and subsequently extract meaningful patterns out of it. While the basic theories and mathematical models of information retrieval and web mining are covered, the Course Description: is primarily focused on practical algorithms of textual document indexing, relevance ranking, web usage mining, text analytics, as well as their performance evaluations.

Introduction to Data mining. Relationship to machine learning. Summarization and feature extraction.Data Preprocessing: Introduction to  preprocessing. Data summarization. Date cleaning. Data integration, Data transformation. Data cube aggregation, attribute subset selection, Dimensionality reduction, Numerosity reduction. Data Discretization, Concept Hierarchy generation.

Postings size estimation, sort-based indexing, dynamic indexing, positional indexes, n-gram indexes, distributed indexing

Inverted indices and Boolean queries. Query optimization. The nature of unstructured and semi-structured text.The term vocabulary and posting lists. Text encoding: tokenization, stemming, lemmatization, stop words, phrases. Optimizing indices with skip lists. Proximity and phrase queries.Positionalindices.Dictionaries and tolerant retrieval.Dictionary data structures. Wild-card queries, permuterm indices, n-gram indices. Spelling correction and synonyms: edit distance, soundex, language detection.

Term weighting, and the vector space model. Parametric or fielded search.Documentzones.The vector space retrieval model.tf.idf weighting. The cosienmeasure.Scoringdocuments.  Map Reduce: Distributed file systems, Map and reduce tasks. Algorithms that use map-reduce: Matrix vector multiplication, Relational algebra operations. Mining Frequent Patterns and Associations: Near-neighbor search, Collaborative filtering, Shingling. Min-hashing and locality  sensitive hashing.

The stream data model, examples of stream sources and queries, sampling data in a stream. Filtering streams, bloom filters, counting distinct elements in a stream. Market-Basket model, Association rules. A-priori algorithm.Classification: Introduction to text classification. Naïve Baye’s models. Spam filtering. K nearest neighbors, Decision boundaries, vector space classification using centroids.Comparative results. Support vector machine classifiers. Kernel function.Evaluation of classification.Micro-and macro-averaging.Learning rankings.

Introduction to the problem.Partitioning methods: K-means clustering; Hierarchical clustering.Latent semantic indexing (LSI).Applications to clustering and to information retrieval.Web Mining: Introduction to  web . Web search overview, web structure, the user, paid placement, search engine optimization/spam. Web measurement.Crawling and web indexes.Near-duplicate detection.Linkanalysis.Web as a graph.PageRank.Machine learning techniques for ranking.

[2].      AnandRajaraman and Jeffery D.ullman, “Mining the Massive”,Cambridge University Press, 2008.

[2].      K.P Soman, Shyamdiwakar and VAjay, “Insight into Data Mining – Theory and Practice”, 6th Ed  print, PHI India, 2012.

[3].      Jiawei Han and MichelineKamber, “Data Mining: Concepts and Techniques”, 2nd Edition,      2006, Morgan Kaufmann Publishers, San Francisco, USA.

The main objective of the course is designed to introduce the core concepts of data mining and data warehousing techniques and implementation

Basic elements of the Data Warehouse: Source system-Data staging Area-Presentation Server-Dimensional Model-Business process-Data Mart-Data warehouse-Operational Data Store-OLAP: ROLAP, MOLAP and HOLAP. DataWarehouse Design:The case for dimensional modeling – Putting Dimensional modeling together: the data warehouse bus architecture – Basic dimensional modeling techniques.

The value of architecture – An architectural framework and approach – Technical architecture overview – Back room data stores – Back room services. Back Room Services. Data Staging:Data staging overview – Plan effectively – Dimension Table staging – Fact Table loads and warehouse operations – Data quality and cleansing – issues.

Data Mining – Process and architecture - Kinds of Data to be mined - Data Mining Functionalities, Classification of Data Mining Systems, Data Mining Task Primitives, Major Issues in Data Mining. Data Preprocessing:Preprocessing - Descriptive Data Summarization – Measuring the central tendency- Measuring the dispersion of data - Data Cleaning - Missing Values – Noisy Data - Data Cleaning as a Process - Data Integration and Transformation - Data Reduction-Data Cube Aggregation-Attribute Subset Selection. Demo: Preprocessing can be done using WEKA tool.

Association Rule Mining: Basic Concepts, Efficient and Scalable Frequent Item set Mining Methods – Apriori algorithm, Generating Rules – Improving efficiency – Mining frequent item set without candidate generation. Classification and Prediction: Issues Regarding Classification and Prediction, Accuracy and Error Measures.Cluster Analysis:Types of Data in Cluster Analysis, A Categorization of Major Clustering Methods, Partitioning Methods – K-Means and K-Medoids, Hierarchical Methods  Agglomerative and Divisive

Demo: Classification and clustering analysis can be done using WEKA tool.

Mining Time-Series Data – Trend analysis – Similarity search, Spatial Data Mining-Spatial Data Cube Construction and Spatial OLAP- Mining Spatial Association and Co-location Patterns-Spatial Clustering, Classification Methods-Mining Raster Databases. Applications and Trends in Data Mining: Data Mining Applications, Data Mining System Products and Research Prototypes, Social Impacts of Data Mining.

[2].    Jiawei Han and MichelineKamber, “Data Mining: Concepts and Techniques”, Morgan Kaufmann Publishers, San Francisco, USA, 2nd Edition, 2011.

[2].      Margaret H. Dunham, “Data mining-Introductory and Advanced topics”, Pearson       Education, 2003.

[3].      Witten and E. Frank, “Data Mining : Practical Machine Learning Tools and        Techniques”, Morgan Kaufmann Publishers, 2005.

[4].      K P Soman, Shyam Diwakar, V. Ajay,“Insight into Data Mining-Theory and  Practice”, 6thReprint, PHI, 2012.

ESE:  40%

This course provides insight on the administrative tasks, their implementation and effective usage of tools.

Introduction: General Definition of DBA and Security, System Management & Database Design Roles of DBA – DBA Job Classification. Types of Databases: Online Transaction Processing System and Decision Support System Databases, Development, Test & Production Databases. Daily Routine of a DBA.Architecture: Database Structures- Logical & Physical, Trace Files, Data Files &Tablespaces, Oracle Managed Files. Processes- Interaction between User & Oracle Processes, The Server Process, Background Processes. Memory Structures- SGA, PGA. Oracle Transactions- Anatomy of SQL Transactions. Data Consistency & Concurrency- Database Writer & Write Ahead Protocol, The System Change Number, Undo Management. Backup and Recovery Architecture-User managed, RMAN, Flashback Techniques. Data Dictionary and Dynamic Performance Views- Data Dictionary, V$ views.

Installing Oracle 11g: Following OFA, System and Owners Pre-Installation Tasks, Installing Software, System Administrator and Oracle Owner’s Post-Installation Tasks, Uninstalling Oracle 11g.Database Creation: Creating SPFILE and pfile, Initialization Parameters, Creating a new Database, Using SPFILE, Starting up and Shutting Down Database

Database Connectivity and Networking: Working of Oracle Network – instance names, global database names, connect descriptors, identifiers and strings, Establishing Connectivity, Oracle Client, Installing the Client, Naming and Connectivity – Local, Easy connect, External and Directory naming methods. 

Managing Users: Creating, altering and dropping users, Creating user Profiles & Resources, Database Resource Manager, Controlling Access to Data – Roles, Privileges and using Views, Stored Procedures to Manage Privileges, Auditing Database – Standard Auditing, Authentication – Database, External, Centralized user and Proxy Authentication. Database Security Do’s & Don’ts-User Accounts, Passwords, OS authentication, Auditing Database, Granting Appropriate Privileges, Permissions, Application Security.

Loading and Transforming Data: Overview of extraction loading and Transformation, Loading Data-Using the SQL Loader Utility, Using External Tables to Load Data. Overview of Common Techniques used for Transforming Data.Data Pump Technology: Introduction, Benefits, Uses and Components of Data Pump.Access method, Data Pump Files, Privileges, Mechanics of Data Pump Job. 

Backing Up Oracle Databases: Backup Terms, Guidelines, Strategies, Examining Flash Recovery Area – benefits of Flash recovery Area, Looking into Flash Recovery Area, Setting size of Flash Recovery Area Creating Flash Recovery Area, Backing up Flash Recovery Area, RMAN – Benefits, Architecture, Connecting to RMAN. SQL Query Optimization:Approach to Performance Tuning, Optimizing Oracle Query Processing, Cost-based Optimizer, Drawbacks of CBO. SQL Performance Tuning Tools – EXPLAIN PLAN, Auto trace, SQL Trace and TKPROF. Tuning the instance:  Introduction, Automatic Tuning vs. Dynamic Views. Tuning Oracle Memory:

Self Learning:

Tuning Shared Pool – Library Cache, Dictionary Cache, Hard vs. Soft Parsing, Sizing Shared Pool, Tuning Buffer Cache – Sizing buffer Cache, Multiple pools for Buffer Cache.

[2].      Kyte and Thomas, “Expert Oracle”, Oracle Press Publication, Signature Edition, 2005.

CIA 60% 

The course is designed to provide a real-world project development and deployment environment for the students.

*The Web Stack Development practical implementation will be executed in the Specialization Lab

List of Programs                                                                                                      

1.   Develop static pages for a given scenario using HTML

2.   Creating Web Animation with audio using HTML5 & CSS3

3.   Demonstrate Geolocation and Canvas using HTML5

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

5.   Demonstrate XSL with XSD

6.   Demonstrate DOM parser

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

8.  Create a web application using AngularJS with Forms.

9.   Implement a single page web application using AngularJS.

10.  CRUD Operation using AngularJS

11.  Implement web application using AJAX with JSON

12.  Demonstrate to fetch the information from an XML file with AJAX

13.  Demonstrate Node.js file system module

14.  Demonstrate Node.js events 

15.  Implement Mysql with Node.JS

16.  Implement CRUD Operation using MongoDB