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R.V. College of Engineering - Bengaluru-560059

RV COLLEGE OF ENGINEERING®

(Autonomous Institution Affiliated to VTU, Belagavi)R.V. Vidyaniketan Post, Mysore Road

Bengaluru – 560 059

Scheme and Syllabus of III & IVSemesters

(Autonomous System of 2018 Scheme)

Master of Technology (M.Tech)in

SOFWARE ENGINEERING

DEPARTMENT OF

INFORMATION SCIENCE &ENGINEERING

Information Science & Engineering


R.V.COLLEGE OF ENGINEERING(Autonomous Institution Affiliated to VTU, Belagavi)

R.V. Vidyaniketan Post, Mysore RoadBengaluru – 560 059

Scheme and Syllabus of III & IVSemesters

(Autonomous System of 2018 Scheme)

Master of Technology (M.Tech)in

SOFTWARE ENGINEERING

DEPARTMENT OF

INFORMATION SCIENCE &ENGINEERING



ABBREVIATIONS

Sl. No. Abbreviation Meaning1. VTU Visvesvaraya Technological University2. BS Basic Sciences3. CIE Continuous Internal Evaluation4. CS Computer Science and Engineering5. CV Civil Engineering6. CHY Chemistry7. EC Electronics and Communication Engineering8. EE Electrical and Electronics Engineering9. ES Engineering Science10. HSS Humanities and Social Sciences11. ME Mechanical Engineering12. PHY Engineering Physics13. SEE Semester End Examination14. MAT Engineering Mathematics 15. PCE Professional Core Elective16. GE Global Elective

INDEXIII Semester

Sl. No. Course Code Course Title Page No.1. 18MSE31 Social Network Analysis

GROUP E: CORE ELECTIVES1. 18MIT3E1 Mobile Application Development 2. 18 MSE 3E2 Web Intelligence 3. 18 MSE 3E3 Natural Language Processing



R V COLLEGE OF ENGINEERNG, BENGALURU-560 059(Autonomous Institution Affiliated to VTU, Belagavi)

DEPARTMENT OF INFORMATION SCIENCE &ENGINEERING

M.Tech in SOFTWARE ENGINEERING

THIRD SEMESTER CREDIT SCHEME

Sl.No.

CourseCode

Course Title BoSCredit Allocation

L T PTotal

Credits

1 18MSE31Social Network

AnalysisIS 4 1 0 5

2 18 MSE 3EX Elective 6 IS 4 0 0 4

3 18 MSE 33 Internship IS 0 0 5 5

4 18 MSE 34 Dissertation Phase I IS 0 0 5 5

Total number of Credits 08 01 10 19

Total Number of Hours / Week 08 2 24

FOURTH SEMESTER CREDIT SCHEME

Sl.No.

CourseCode

Course Title BoSCredit Allocation

L T PTotal

Credits

1 18MSE41 Dissertation Phase II IS 0 0 20 20

2 18MSE42 Technical Seminar IS 0 0 2 2

Total number of Credits 0 0 22 22

Total Number of Hours / Week



Semester: IIISocial Network Analysis

(Theory)Course Code: 18MSE31 CIE Marks: 100Credits: L:T:P:S: 4:1:0:0 SEE Marks: 100Hours: 48L+24T SEE Duration: 3HrsCourse Learning Objectives: 1 List basic principles behind network analysis algorithms2 Acquire essential knowledge of network analysis3 Apply real world data with examples from today’s most popular social networks.4 Engage in critical thinking regarding the applicability of social network theory to various

sociological phenomena.

Unit-ISocial Network Analysis: History, Concepts, and Research: Introduction, SNA Definition and features, The Development of Social Network Analysis: A Brief History, Basic Concepts and Research of SNA: Design, Theorization, and Data Processing.Social Network Analysis: What is network analysis? , Development of Social Network , Key concepts andmeasures in network analysis

07 Hrs

Unit – IIOnline Identities and Social Networking: Introduction , Background on Digital Identities, Putting Social Relations to Work, Social Digital Identity, Information and Threats in Social NetworksDiscovering Sets of Key Players in Social Networks :Information Theory in SNA, Methods for Discovering Sets of Key Players, Discovering Sets of Key Players Using Entropy Measures

07 Hrs

Unit –IIIDecentralized Online Social Networks:Introduction, Challenges for DOSN, The Case for Decentralizing OSNs, General PurposeDOSNs, Specialized Application Centric DOSNs, Delay-Tolerant DOSNUnderstanding and Predicting Human Behavior for Social Communities:Introduction, User Data Management, Inference and Distribution, Enabling New Human Experiences, The Social Enabler, Applications

07 Hrs

Unit –IVSecurity and Privacy in Online Social Networks:Introduction, Security Objectives: Privacy, Integrity, and Availability, Attack Spectrum andCountermeasures. Optimizing Targeting of Intrusion Detection Systems in Social Networks:Introduction, Background, Epidemic Propagation in Social Networks.Security Requirements for Social Networks:Introduction, Context, Threats, and Incidents, Two patterns

08 Hrs

Unit –VVisualization and applications of social networks : Graph theory , Centrality , Clustering ,Node-Edge Diagrams , Matrix representation ,Visualizing online social networks, Visualizing social networks with matrix-basedrepresentations , Matrix and Node-Link Diagrams, Hybrid representations ,Applications ,Cover networks , Community welfare ,Collaboration networks , Co-Citationnetworks.

07 Hrs



Course Outcomes: After completing the course, the students will be able toCO1:

Comprehend basic notation, concepts and terminology used in network science.

CO2:

Visualize, Analyze, summarize and compare different networks and its security.

CO3:

Use relevant tools to analyze real world networks

CO4:

Use advanced network analysis methods to perform empirical investigations of network data.

Reference Books

1 “Social Networks and the Semantic Web”, Peter Mika, First Edition, Springer. ISBN-13:978-0-387-71000-6

2 “Handbook of Social Network Technologies and Applications”, BorkoFurht, 1st Edition, ,2010, Springer, ISBN 978-1-4419-7141-8

3 “Computational Social Network Analysis- Trends, Tools and Research Advances”, AjithAbraham ,Aboul-Ella Hassanien, Springer, ISBN 978-1-84882-228-3

4 Social Network Data Analytics , ‖ Charu C. Aggarwal, 2014, Springer; ISBN 978-1-4419-8462-3

Scheme of Continuous Internal Evaluation (CIE); Theory (100 Marks):

CIE is executed by way of quizzes (Q), tests (T) and assignments. A minimum of two quizzes areconducted and each quiz is evaluated for 10 marks adding up to 20 marks. Faculty may adoptinnovative methods for conducting quizzes effectively. The three tests are conducted for 50 marks eachand the sum of the marks scored from three tests is reduced to 50 marks. A minimum of twoassignments are given with a combination of two components among 1) Solving innovative problems2) Seminar/new developments in the related course 3) Laboratory/ field work 4) mini project.

Total CIE is 20+50+30 = 100 marks.

Scheme of Semester End Examination (SEE) for 100 marks:

The question paper will have FIVE questions with internal choice from each unit. Each question will carry 20 marks. Student will have to answer one full question from each unit.



Semester: IIIMobile Application Development

(Elective)Course Code: 18MIT3E1 CIE Marks: 100Credits: L:T:P:S: 4:0:0:0 SEE Marks: 100Hours: 48L SEE Duration: 3HrsCourse Learning Objectives: 1 Comprehend the knowledge on essentials of mobile application development.2 Demonstrate the basic and advanced features of Android technology.3 Develop the skills in designing and building mobile applications using Android platform.4 Create debug and publish innovative mobile applications using Android platform

Unit-IEssentials For Mobile Application DevelopmentBackground about mobile technologies, Overview of Android, Android architecture,Android for mobile application development, Android development Framework – AndroidSDK, Emulators / Android AVD Android Project Framework , Setting up developmentenvironment, Running android app, Dalvik Virtual Machine & .apk file extension, androiddebug bridge. Fundamentals: Basic Building blocks - Activities, Services, BroadcastReceivers & Content providers, UI Components - Views & notifications, Components forcommunication -Intents & Intent Filters, Android API levels (versions & version names)

10 Hrs

Unit – IIAndroid UI Architecture & UI WidgetsApplication context, Intents, Activity life cycle, Supporting different devices, multiplescreen sizes, Fundamental Android UI design – Layouts, Drawable resources, UI widgets,Notification, Toasts, Menu, Dialogs, Lists & Adapters, Building dynamic UI withfragments.

09 Hrs

Unit –IIIData Storage, Services & Content ProvidersSaving Data, Interacting with other Applicationss, Working with system permissions,Applications with content sharing, Shared Preferences, Preferences activity, Files access,SQLite database, Threads, Overview of services in Android, Implementing a Service,Service lifecycle, Inter Process Communication.

10 Hrs

Unit –IVAdvanced AndroidBuilding apps with Multimedia, Building apps with Graphics & Animations, Building appswith Location Based Services and Google maps, Building apps with Connectivity & Cloud,Sensors, Bluetooth, Camera, Telephony Services.

10Hrs

Unit –VTesting, Debugging & Deployment of Android ApplicationRole and use of Dalvik Debug Monitor Server (DDMS), adb tool, How to debug Androidapplication, Use of Step Filters, Breakpoints, Suspend and Resume, How to use LogCat,Preparing for publishing – Signing & Versioning of apps, Using Google Play to distribute& Monetize, Best practices for security & privacy.

09 Hrs




Comprehend the basic features of Android Platform and the Application DevelopmentProcess. Acquire familiarity with basic building blocks of Android Application and itsarchitecture.

CO2:

Apply and explore the basic framework, usage of SDK to build apps incorporating Androidfeatures in developing mobile applications.

CO3:

Demonstrate proficiency in coding on a mobile programming platform using advancedAndroid technologies like multimedia, involving the sensors and hardware features of thephone.

CO4:

Demonstrate proficiency in testing, debugging and deployment of Android applications.

Reference Books

1Android Programming, Phillips, Stewart, Hardy and Marsicano, 2nd edition, 2015; Big NerdRanch Guide; ISBN-13 978-0134171494

2Professional Android 2 Application Development; Reto Meier; 1st Edition; 2012;Wiley IndiaPvt.ltd; ISBN-13: 9788126525898

3Beginning Android 3; Mark Murphy; 1st Edition; 2011; A press Springer India Pvt Ltd. ;ISBN-13: 978-1-4302-3297-1

4Android Programming – Pushing the limits by Hellman; Eric Hellman; Wiley; 2013; ISBN13: 978-1118717370








Semester: IIIWeb Intelligence

(Elective)Course Code: 18MSE3E2 CIE Marks: 100Credits: L:T:P:S: 4:0:0:0 SEE Marks: 100Hours: 48L SEE Duration: 3HrsCourse Learning Objectives: 1 To understand different issues and approaches related to web Intelligence.2 To learn various web mining techniques with applications like Web Content Mining, Web

Structure Mining and Web Usage Mining.3 To learn the application of web services in Ubiquitous Computing.4 To explore the fundamental concepts on knowledge representation and Ontological

Engineering.

Unit-IIntroduction to Web Intelligence: What is Web Intelligence?, Benefits of Intelligent Web, Ingredients of Web Intelligence,Topics of Web Intelligence, Related Technologies.Information Retrieval: Document Representation, Retrieval Models, Evaluation ofRetrieval Performance

08 Hrs

Unit – IISemantic Web: The Layered-Language Model, Metadata and Ontologies, Ontology Languages for theWeb. Data Mining Techniques: Classification and Association, Clustering

08 Hrs

Unit –IIIWeb Usage Mining: Web-Log Processing, Analyzing Web Logs, Applications of Web Usage Mining,Clustering of Web Users, Classification Modeling of Web Users, Association Mining ofWeb Usages, Sequence-Pattern Analysis of Web Logs

08 Hrs

Unit –IVWeb Content Mining: Web Crawlers, Search Engines, Personalization of Web Content, MultimediaInformation Retrieval

07 Hrs

Unit –VWeb Structure Mining: Modeling Web Topology, PageRank Algorithm, Hyperlink-Induced Topic Search(HITS), Random Walks on the Web, Social Networks, Reference and Index Pages

08 Hrs


Inspect the models of information retrieval, semantic webs, search engines, and web mining.

CO2:

Apply data mining tools to develop projects in web mining and information retrieval.

CO3:

Gain the knowledge of fundamental concepts on knowledge representation and OntologicalEngineering.

CO4:

Apply of Web Intelligence on the Social Web



Reference Books

1Building an Intelligent Web: Theory and Practice. Akerkar, R. &Lingras, P. (2008). Jonesand Bartlett Publishers, Sudbury, Massachusetts. ISBN-13: 978-0-7637-4137-2

2Data Mining: Practical Machine Learning Tools and Techniques. Witten, Ian H. & Frank, E.2nd Edition, 2005, Morgan Kaufman. ISBN 0120884070, 9780120884070

3Advanced Techniques in Web Intelligence – 1, Juan D.Vel´asquez and Lakhmi C. Jain (Eds.):Sep-2010, Springer,.

4Evolution of the Web in Artificial IntelligenceEnvironments, RichiNayak, NikhiIchalkaranje,Lakhmi C. Jain: 2008,Springer.








Semester: IIINatural Language Processing

(Elective)Course Code: 18MSE3E3 CIE Marks: 100Credits: L:T:P:S: 4:0:0:0 SEE Marks: 100Hours: 48L SEE Duration: 3HrsCourse Learning Objectives: 1 Demonstrate sensitivity to linguistic phenomena and an ability to model them with formal

grammars.2 Train and evaluate empirical NLP systems3 Manipulate probabilities, construct statistical models over strings and trees, and estimate

parameters using supervised and unsupervised training methods4 Design, implement, and analyze NLP algorithms

Unit-IOverview and Language Modeling: Overview: Origins and challenges of NLP-Language and Grammar-Processing IndianLanguages- NLP Applications -Information Retrieval. Language Modeling: VariousGrammar- based Language Models - Statistical Language ModelAccessing Text Corpora Accessing Text Corpora, Conditional Frequency Distributions

10 Hrs

Unit – IIProcessing Raw Text : Accessing Text from the Web and from Disk, Strings: Text Processing at the Lowest LevelText Processing with Unicode, Regular Expressions for Detecting Word Patterns, UsefulApplications of Regular Expressions, Normalizing Text ,Regular Expressions forTokenizing Text, Segmentation, Formatting: From Lists to Strings

09 Hrs

Unit –IIICategorizing and Tagging Words : Using a Tagger, Tagged Corpora, Mapping Words to Properties Using Python DictionariesAutomatic Tagging, N-Gram Tagging, Transformation-Based Tagging, How to Determinethe Category of a WordLearning to Classify Text : Supervised Classification, Further Examples of Supervised Classification, Evaluation,Decision Trees, Naive Bayes Classifiers and other machine Learning models.

10 Hrs

Unit –IVExtracting Information from the text : Information Extraction, Chunking, Developing and Evaluating Chunkers, Recursion inLinguistic Structure, Named Entity Recognition, Term weighting, Inverse documentfrequency, Residual inverse document frequencyAnalyzing Sentence Structure : Some Grammatical Dilemmas, What’s the Use of Syntax?, Context-Free Grammar, Parsingwith Context-Free Grammar, Dependencies and Dependency Grammar, GrammarDevelopment.

10 Hrs

Unit –VAnalyzing the Meaning of words and Sentences : The semantics of English sentences, Representing Meaning, Semantic Analysis, Lexical

09 Hrs



semantics, Word-sense disambiguation, Supervised – Dictionary based and UnsupervisedApproaches, Compositional semantics, Semantic Role Labelling and Semantic ParsingApplications of NLP- Spell-checking, SummarizationInformation Retrieval- Vector space model, term weighting, homonymy, polysemy,synonymy, improving user queries.Machine Translation– Overview.


Understand the approaches to syntax and semantics in Natural Language Processing, the various types of language processors, the elements of formal language theory, the types of grammar, and the computational morphology.

CO2:

Understand the basic parsing technique for context-free grammars, the data structures and algorithms for parsing, and the approaches to ambiguity resolution.

CO3:

Apply the fundamental algorithms and techniques in the area of Natural Language Processing.

CO4:

Comprehend and compare different natural language models.

Reference Books1 “Artificial Intelligence (SIE)”, Kevin Night and Elaine Rich, Nair B., McGraw Hill- 2008.2 “Introduction to AI and ES”, Dan W. Patterson, 2007, Pearson Education.3 “Introduction to Expert Systems”, Peter Jackson, 3rd Edition, 2007,Pearson Education.4 “Artificial Intelligence”, Deepak Khemani ,Tata McGraw Hill Education 2013.








INTERNSHIP Course Code : 18MSE33 CIE Marks : 100Credits : L:T:P 0:0:5 SEE Marks : 100

Hours/week : 10 SEE Duration : 3 HrsGUIDELINES FOR INTERNSHIP

Course Learning Objectives (CLO):The students shall be able to:(1) Understand the process of applying engineering knowledge to produce product and provide

services. (2) Explain the importance of management and resource utilization(3) Comprehend the importance of team work, protection of environment and sustainable solutions. (4) Imbibe values, professional ethics for lifelong learning.

1) The duration of the internship shall be for a period of 8 weeks on full time basis between II semesterfinal exams and beginning of III semester.

2) The student must submit letters from the industry clearly specifying his / her name and the duration ofthe internship on the company letter head with authorized signature.

3) Internship must be related to the field of specialization or the M.Tech program in which the student hasenrolled.

4) Students undergoing internship training are advised to report their progress and submit periodicprogress reports to their respective guides.

5) Students have to make a presentation on their internship activities in front of the departmentalcommittee and only upon approval of the presentation should the student proceed to prepare andsubmit the hard copy of the internship final report. However interim or periodic reports and reports asrequired by the industry / organization can be submitted as per the format acceptable to the respectiveindustry /organizations.

6) The reports shall be printed on bond paper – 80GSM, back to back print, with soft binding – A4 sizewith 1.5 spacing and times new roman font size 12.

7) The broad format of the internship final report shall be as follows Cover Page Certificate from College Certificate from Industry / Organization Acknowledgement Synopsis Table of Contents Chapter 1 - Profile of the Organization – Organizational structure, Products, Services,

Business Partners, Financials, Manpower, Societal Concerns, Professional Practices, Chapter 2 - Activities of the Department - Chapter 3 – Tasks Performed – summaries the tasks performed during 8 week period Chapter 4 – Reflections – Highlight specific technical and soft skills that you acquired during

internship



References & Annexure

Course Outcomes:After going through the internship the student will be able to:CO1: Apply engineering and management principlesCO2: Analyze real-time problems and suggest alternate solutionsCO3: Communicate effectively and work in teamsCO4: Imbibe the practice of professional ethics and need for lifelong learning.

1. Scheme of Continuous Internal Evaluation (CIE):A committee comprising of the Head of the Department / Associate Dean, Associate Professor, AssistantProfessor and Guide would review the presentation and the progress reports in two phases. The evaluationcriteria shall be as per the rubrics given below: Scheme for Semester End Evaluation (SEE):The evaluation will be done by ONE senior faculty from the department and ONE external faculty memberfrom Academia / Industry / Research Organization. The following weightages would be given for theexamination. Evaluation will be done in batches, not exceeding 6 students.

(1) Explanation of the application of engineering knowledge in industries 35%

(2) Ability to comprehend the functioning of the organization/ departments 20%

(3) Importance of resource management, environment and sustainability 25%

(4) Presentation Skills and Report 20%



Dissertation Phase 1

Course Code : 18MSE34 CIE Marks : 100

Credits : L:T:P 0:0:5 SEE Marks : 100

Hours/week : 10 SEE Duration : 3 HoursCourse Learning Objectives:The students shall be able to1. Understand the method of applying engineering knowledge to solve specific problems. 2. Apply engineering and management principles while executing the project3. Demonstrate good verbal presentation and technical report writing skills.4. Identify and solve complex engineering problems using professionally prescribed standards.

GUIDELINES 1. Major project will have to be carried out by only one student in his/her area of interest. 2. Each student has to select a contemporary topic that will use the technical knowledge of their

program of specialization. 3. Allocation of the guides preferably in accordance with the expertise of the faculty. 4. The project can be carried out on-campus or in an industry or an organization with prior approval

from the Head of the Department.5. The standard duration of the project is for 16 weeks, however if the guide and the evaluation

committee of the department, after the assessment feel that the work is insufficient and it has to beextended, then the student will have to continue as per the directions of the guide and the committee.

6. It is mandatory for the student to present his/her work in one of the international conferences orpublish the research finding in a reputed unpaid journal with impact factor.

Course Outcomes: After going through this course the students will be able toCO1: Conceptualize, design and implement solutions for specific problems. CO2: Communicate the solutions through presentations and technical reports. CO3: Apply project and resource managements skills, professional ethics, societal concerns CO4: Synthesize self-learning, sustainable solutions and demonstrate life-long learning

Scheme of Continuous Internal Examination (CIE)Evaluation will be carried out in THREE Phases. The evaluation committee will comprise of: guide,two senior faculty members, one industry member and Head of the Department.

Phase Activity Weightage4th week Topic approval along with Synopsis 20%8th week Literature survey with Problem Statement 20%12th week Motivation and Objectives 20%15th week Preliminary report for the approval of selected topic along with

methodology.40%

CIE Evaluation shall be done with marks distribution as follows: Selection of the topic 10% Literature review and framing of objectives 25%



Defining the brief methodology along with thealgorithm development/experimental setup 25%

Presentation 20% Report writing 20%

Scheme for Semester End Evaluation (SEE):The evaluation will be done by ONE senior faculty from the department and ONE external facultymember from Academia / Industry / Research Organization. The following weightages would be givenfor the examination. Evaluation will be done in batches, not exceeding 6 students.

1. Brief write-up about the project 5%2. Formulation of Project Objectives & Methodology 20%3. Presentation 25%4. Report 20%5. Viva Voce 30%



SEMESTER IV

Dissertation Phase II

Course Code : 18MSE41 CIE Marks : 100

Credits : L:T:P 0:0:20 SEE Marks : 100

Hours/Week : 40 SEE Duration : 3 HoursCourse Learning Objectives:The students shall be able to1. Understand the method of applying engineering knowledge to solve specific problems. 2. Apply engineering and management principles while executing the project3. Demonstrate good verbal presentation and technical report writing skills.4. Identify and solve complex engineering problems using professionally prescribed standards.

GUIDELINES 1. Major project will have to be done by only one student in his/her area of interest. 2. Each student has to select a contemporary topic that will use the technical knowledge of their program

of specialization. 3. Allocation of the guides preferably in accordance with the expertise of the faculty. 4. The project can be carried out on-campus or in an industry or an organization with prior approval from

the Head of the Department.5. The standard duration of the project is for 16 weeks, however if the guide and the evaluation committee

of the department, after the assessment feel that the work is insufficient and it has to be extended, thenthe student will have to continue as per the directions of the guide and the committee.

6. It is mandatory for the student to present his/her work in one of the international conferences or publishthe research finding in a reputed unpaid journal with impact factor.

Course Outcomes: After going through this course the students will be able toCO1: Conceptualize, design and implement solutions for specific problems. CO2: Communicate the solutions through presentations and technical reports. CO3: Apply project and resource managements skills, professional ethics, societal concerns CO4: Synthesize self-learning, sustainable solutions and demonstrate life-long learning

Scheme of Continuous Internal Examination (CIE)Evaluation will be carried out in THREE Phases. The evaluation committee will comprise of: guide,two senior faculty members, one industry member and Head of the Department.

Phase II Activity Weightage5th week Review and refinement of Objectives and methodology. 20%10th week Mid-term progress review shall check the compliance with the objectives

and methodology presented in Phase I, review the work performed. 40%

15th week Oral presentation, demonstration and submission of project report.Outcome and publication

40%

CIE Evaluation shall be done with marks distribution as follows: Review of formulation of objectives and methodology 10% Design and simulation/ algorithm development/experimental setup 25%



Conducting experiments / implementation / testing / analysis 25% Demonstration & Presentation 20% Report writing 20%

Scheme for Semester End Evaluation (SEE):The evaluation will be done by ONE senior faculty from the department and ONE external facultymember from Academia / Industry / Research Organization. The following weightages would be givenfor the examination. Evaluation will be done in batches, not exceeding 6 students.

1. Brief write-up about the project 5%2. Formulation of Project Objectives & Methodology 20%3. Experiments / Analysis Performed; Results & Discussion 25%4. Report 20%5. Viva Voce 30%



TECHNICAL SEMINAR Course Code : 18MSE42 CIE Marks : 50Credits : L:T:P 0:0:2 SEE Marks 50

Hours/Week : 4 SEE Duration 30 min

Course Learning Objectives (CLO):The students shall be able to:

(1) Understand the technological developments in their chosen field of interest(2) Explain the scope of work and challenges in the domain area(3) Analyze these engineering developments in the context of sustainability and societal

concerns.(4) Improve his/her presentation skills and technical report writing skills

GUIDELINES1) The presentation will have to be done by individual students. 2) The topic of the seminar must be in one of the thrust areas with in-depth review and analysis on a

current topic that is relevant to industry or on-going research.3) The topic could be an extension or complementary to the project 4) The student must be able to highlight or relate these technological developments with sustainability

and societal relevance. 5) Each student must submit both hard and soft copies of the presentation.

Course Outcomes:After going through this course the student will be able to:CO1: Identify topics that are relevant to the present context of the world CO2: Perform survey and review relevant information to the field of study.CO3: Enhance presentation skills and report writing skills.CO4: Develop alternative solutions which are sustainable

Scheme of Continuous Internal Evaluation (CIE): Evaluation would be carried out in TWO phases. Theevaluation committee shall comprise of Head of the Department / Associate Dean, Associate Professor,Assistant Professor and Guide. The evaluation criteria shall be as per the rubrics given below:

Scheme for Semester End Evaluation (SEE):The evaluation will be done by ONE senior faculty from the department and ONE externalfaculty member from Academia / Industry / Research Organization. The following weightageswould be given for the examination. Evaluation will be done in batches, not exceeding 6students.


Rubrics for Evaluation: 1) Topic – Technical Relevance, Sustainability and Societal Concerns 15%

2) Review of literature 25%

3) Presentation Skills 35%

4) Report 25%


Curriculum Design Process

Academic Planning And Implementation



Process For Course Outcome Attainment

Final CO Attainment Process



Program Outcome Attainment Process



PROGRAM OUTCOMES (PO)

M. Tech. in Information Technology Students will be able to:

PO1: An ability to independently carry out research /investigation and development work to solve

practical problems.

PO2: An ability to write and present a substantial technical report/document.

PO3: Acquire in-depth knowledge of information technology with global perspective, analyze &

synthesize with existing and new knowledge to enhance the skills.

PO4: Apply appropriate techniques to use modern engineering & IT tools by analyzing its limitations.

PO5: Recognise opportunities and contribute positively to collaborative-multidisciplinary scientific

research in Information Technology, demonstrate a capacity for self-management and teamwork.

PO6: Demonstrate knowledge and understanding of Information Technology principles & apply the

same to one’s own work, as a member and leader in a team, manage projects efficiently.


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