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B.Tech in Computer Science and Engineering With Specialization in Cyber Security/ Data Analytics/ AI & ML

 

Computer Science College in India

COURSE OFFERED DURATION (IN YEARS) ELIGIBILITY CRITERIA
B.Tech In Computer Science & Engineering With Specialization In Cyber Security/ Data Analytics/ AI & ML 4 12th standard pass with Physics, Maths, Chemistry/ Computer Science with at least 60% marks.
M.Tech in Computer Science & Engineering With  Specialization In Cyber Security/ Data Analytics/ AI & ML 2  

Disclaimer: TNU reserves the right for relaxation in admission criteria for the most deserving candidates.

Computer Science and Engineering seems to have become the most popular course in this century for engineering aspirants. With rapid rise in cyber-terrorism, misuse of social media and internet usage, our technology security experts think that India is yet not well equipped to handle these threats. Cyber Security market to touch $32 billion by 2025. Expansion will require 1 million (10 lakh) Cyber Security professionals. Bengal hopes to train one lakh Cyber Security experts from the state. - The Telegraph, Saturday, March 17, 2018. Data analytics refers to qualitative, quantitative and statistical techniques & process used to describe and illustrate, condense and recap, and probe large and varied data which is extricated and classified to pinpoint and figure out behavioural uncover hidden patterns, market trends, customer preferences, unknown correlations and other useful information to intensify productivity & can be used to assist organizations for taking more-acquainted business decisions and also help scientists and researchers to verify or disprove scientific models, theories and hypotheses

COURSE STRUCTURE: CYBER SECURITY

Semester 1

Sl No

Type of Course

Course Code

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Basic Science Course

BSC-101

Physics   

3

1

2

5

2

Basic Science Course

BSC-102

Mathematics I [Calculus and Linear Algebra]

3

1

0

4

3

Engineering Science Course

ESC-101

Basic Electrical and Electronics Engineering

3

1

2

5

4

Engineering Science Course

ESC-102

Engineering graphics and design

0

1

4

3

5

Mandatory Course

 

Environmental Science

3

-

-

3

6

Humanities and Social Sciences including Management Course

 

English I

2

0

2

3

 

 

 

No. of hours

14

4

10

23

28 hours                                Total Credits

23

Semester 2

Sl No

Type of Course

Course Code

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

PEC

Fundamentals of Cyber Security

2

0

4

4

2

Basic Science Course

BSC-201

Mathematics II  [Probability and Statistics]

3

1

0

4

3

Engineering Science Course

ESC-201

Programming for Problem Solving

3

1

6

7

4

Engineering Science Course

ESC-202

Workshop / Manufacturing Practices

0

0

4

2

5

Humanities and Social Sciences including Management

HSMC-201

English II

2

0

2

3

6

Open Elective

 

Open Elective I [Constitution of India/ Essence of Indian core knowledge]

3

0

0

3

 

 

 

No. of hours

13

2

16

23

31 hours              Total Credits

23

Semester 3

Sl No

Type of Course

Course Code

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Engineering Science Course

ESC

Web Design and Applications

2

0

4

4

2

Professional Core Courses

PCC-CS 301

Data Structure and Algorithms

3

1

4

6

3

Professional Core Courses

PCC

Digital Electronics    [up to microprocessor basics]

3

0

4

5

4

Professional Core Courses

PCC-CS 302

Discrete Mathematics

3

1

0

4

5

Professional Core Courses

HSMC-301

Numerical Methods

3

0

4

5

 

 

 

No. of hours

14

2

16

24

32 Hours                                         Total Credits

24

Semester 4

Sl No

Type of Course

Course Code

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Core Course

PCC-CS-401

Optimization Techniques

3

1

0

4

2

Professional Core Course

PCC

Computer Organisation & Architecture

3

0

4 Microprocessor Lab (8085 & 8086)

5

3

Professional Core Courses

PCC-CS 403

Operating System

3

0

4

5

4

Professional Core Courses

PCC-CS 404

Object Oriented Programming

3

1

4

6

5

Humanities and Social Sciences including Management

HSMC-401

Management [Organisational Behaviour / Finance & Accounting]

3

0

0

3

 

 

 

No. of hours

15

2

12

23

29 Hours                                          Total Credits

23

Semester 5

Sl No

Type of Course

Course Code

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

PEC

Embedded Systems & Security

3

0

4

5

2

Professional Core Courses

PCC-CS 501

Database Management System

3

0

4

5

3

Professional Core Courses

PCC-CS 502

Compiler Design and Automata Theory

4

0

0

4

4

Professional Core Courses

PCC-CS 602

Computer Network

3

0

4

5

5

Professional Elective Course

PEC-501

Application and System Security

2

0

2

3

6

 

 

Internship

-

-

-

3

 

 

 

No. of hours

15

0

14

25

29hours                                          Total Credits

25

Semester 6

Sl No

Type of Course

Course Code

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Courses

PCC-CS- 601

Cyber crime Investigations and forensics

3

0

4

5

2

Professional Core Course

 

Design and Analysis of Algorithms

3

0

4

5

3

Professional Elective Courses

PEC

Network and System Security

2

0

2

3

4

Professional Elective Courses

PEC

Cryptography (Steganography and Watermarking)

3

0

2

4

5

Humanities and Social Sciences including Management Course

 

Engineering Economics

2

0

0

2

6

Project

PROJ-CS 60

Project I

0

0

6

3

 

 

 

No. of hours

13

0

18

22

31 Hours                                          Total Credits

22

Semester 7

Sl No

Type of Course

Course Code

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Core Course

PCC-CS 702

Image Processing

3

0

4

5

2

Professional Elective Courses

PEC

Security and Emerging Technologies

2

0

4

4

3

Open Elective Courses.

OEC

Open Elective [Communicative English]

3

0

0

3

4

Professional Core Course

 

Software Engineering

3

0

0

3

5

Project

PROJ-CS 70

Project II

0

0

12

6

6

 

 

Internship

-

-

-

3

 

 

 

No. of hours

11

0

20

24

31 Hours                                          Total Credits

24

Semester 8

Sl No

Type of Course

Course Code

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Project

PROJ-CS 80

Project III

0

0

30

15

2

Project

 

Seminar

-

-

-

3

3

Project

 

Grand Viva

-

-

-

3

 

 

 

Total Hours

0

0

30

21

30 Hours                                        Total Credits

21


COURSE STRUCTURE: DATA ANALYTICS

Semester 1

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Basic Science Course

Physics   

3

1

2

5

2

Basic Science Course

Mathematics I [Calculus and Linear Algebra]

3

1

0

4

3

Engineering Science Course

Basic Electrical and Electronics Engineering

3

1

2

5

4

Engineering Science Course

Engineering graphics and design

0

1

4

3

5

Mandatory Course

Environmental Science

3

-

-

3

6

Humanities and Social Sciences including Management Course

English I

2

0

2

3

 

 

No. of hours

14

4

10

 

                                                                             28 hours                                       Total Credits

23

Semester 2

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

Introduction to Data Analytics

3

1

0

4

2

Basic Science Course

Mathematics II  [Probability and Statistics]

3

1

0

4

3

Engineering Science Course

Programming for Problem Solving

3

1

6

7

4

Engineering Science Course

Workshop / Manufacturing Practices

0

0

4

2

5

Humanities and Social Sciences including Management

English II

2

0

2

3

6

Open Elective

Open Elective I [Constitution of India/ Essence of Indian core knowledge]

3

0

0

3

 

 

No. of hours

14

3

12

23

29 hours                                      Total Credits

23

Semester 3

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Basic Science Courses

Statistical Analysis using R

2

1

4

5

2

Professional Core Courses

Data Structure and Algorithms

3

1

4

6

3

Professional Core Courses

Digital Electronics    [up to microprocessor basics]

3

0

4

5

4

Professional Core Courses

Discrete Mathematics

3

1

0

4

5

Professional Core Courses

Numerical Methods

3

0

4

5

 

 

No. of hours

14

3

16

 

33 Hours                                         Total Credits

25

Semester 4

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Core Course

Optimization Techniques

[LPP, Convex Hul, Basis]

3

1

0

4

2

Professional Core Courses

Computer Organisation & Architecture

3

0

4Microprocessor Lab (8085 & 8086)

5

3

Professional Core Courses

Operating System

3

0

4

5

4

Professional Core Courses

Object Oriented Programming

3

1

4

6

5

Humanities and Social Sciences including Management

Management [ Organisation Behaviour / Finance & Accounting]

3

0

0

3

 

 

No. of hours

15

2

12

 

29 Hours                                          Total Credits

23

Semester 5

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

Introduction to Machine Learning 3 0 4 5

2

Professional Core Courses

Database Management System 3 0 4 5

3

Professional Core Courses

Compiler Design and Automata Theory 4 0 0 4

4

Professional Core Courses

Computer Network 3 0 4 5

5

Humanities and Social Sciences including Management Course

Engineering Economics 2 0 0 2

 

 

Intern  ship - - -

3

     No. of hours 15 0 12  
  27hours                                          Total Credits 24

Semester 6

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Courses

Data Mining and Data Warehousing

3

0

4

5

2

Professional Core Course

Design and Analysis of Algorithm

3

0

4

5

3

Professional Elective Courses

Big Data Analytics with Hadoop / Spark

3

0

2

4

4

Professional Elective Courses

Multivariate Analysis, Time Series & Forecasting

 

3

0

4

[Practical : Time Series algo using R]

5

5

Project

Project I

0

0

6

3

 

 

No. of hours

12

0

20

 

32 Hours                                          Total Credits

22

Semester 7

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

Advance Data Analytics

[Text Analysis, Video - Audio- Image Analysis]

4

0

4

6

2

Professional Elective Courses

Data Visualization and Business Analytics

3

0

4

5

3

Open Elective Courses.

Open Elective [Communicative English]

3

0

0

3

4

Professional Core Course

Software Engineering

3

0

0

3

5

Project

Project II

0

0

12

6

6

 

Internship

-

-

-

3

 

 

No. of hours

13

0

20

26

33 Hours                                          Total Credits

26

Semester 8

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Project

Project III

0

0

30

15

2

Project

Seminar

-

-

-

3

3

 

Grand Viva

-

-

-

3

3

 

No. of Hours

0

0

30

21

30 Hours                                        Total Credits

21

COURSE STRUCTURE: AI&ML

Semester 1

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Basic Science Course

Physics   

3

1

2

5

2

Basic Science Course

Mathematics I [Calculus and Linear Algebra]

3

1

0

4

3

Engineering Science Course

Basic Electrical and Electronics Engineering

3

1

2

5

4

Engineering Science Course

Engineering graphics and design

0

1

4

3

5

Mandatory Course

Environmental Science

3

-

-

3

6

Humanities and Social Sciences including Management Course

English I

2

0

2

3

 

 

No. of hours

14

4

10

 

28 hours    Total Credits

23

Semester 2

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

Introduction to AI

3

1

0

4

2

Basic Science Course

Mathematics II  [Probability and Statistics]

3

1

0

4

3

Engineering Science Course

Programming for Problem Solving

3

1

6

7

4

Engineering Science Course

Workshop / Manufacturing Practices

0

0

4

2

5

Humanities and Social Sciences including Management

English II

2

0

2

3

6

Open elective

Open Elective I

Constitution of India/ Essence of Indian core knowledge

3

0

0

3

 

 

No. of hours

14

3

12

 

29 hours              Total Credits

23

Semester 3

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Basic Science Courses

Statistical Analysis using R

2

1

4

5

2

Professional Core Courses

Data Structure and Algorithms

3

1

4

6

3

Professional Core Courses

Digital Electronics    [up to microprocessor basics]

3

0

4

5

4

Professional Core Courses

Discrete Mathematics

3

1

0

4

5

Professional Core Courses

Numerical Methods

3

0

4

5

 

 

No. of hours

14

3

16

 

33 Hours                                         Total Credits

25

Semester 4

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Core Course

Optimization Techniques

[LPP, Convex Hul, Basis]

3

1

0

4

2

Professional Core Courses

Computer Organisation & Architecture

3

0

4Microprocessor Lab (8085 & 8086)

5

3

Professional Core Courses

Operating System

3

0

4

5

4

Professional Core Courses

Object Oriented Programming

3

1

4

6

5

Humanities and Social Sciences including Management

Management [Organisational Behaviour / Finance & Accounting]

3

0

0

3

 

 

No. of hours

15

2

12

 

29 Hours                                          Total Credits

23

Semester 5

 

SLNO

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

Introduction to Machine Learning

3

0

4

5

2

Professional Core Courses

Database Management System

3

0

4

5

3

Professional Core Courses

Compiler Design and Automata Theory

4

0

0

4

4

Professional Core Courses

Computer Network

3

0

4

 

5

5

Humanities and Social Sciences including Management Course

Engineering Economics

2

0

0

2

6

 

Internship

-

-

-

3

 

 

No. of hours

15

0

12

 

27hours                                          Total Credits

24

Semester 6

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Courses

Supervised Learning

3

0

4

5

2

Professional Core Course

Design and Analysis of Algorithm

3

0

4

5

3

Professional Elective Courses

Big Data Analytics with Hadoop / Spark

3

0

2

4

4

Professional Elective Courses

Unsupervised Learning

 

3

0

4

5

5

Project

Project I

0

0

6

3

 

 

No. of hours

12

0

20

 

32 Hours                                          Total Credits

22

Semester 7

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

Natural Language Processing

4

0

4

6

2

Professional Elective Courses

Data Pre-Processing and Visualization

3

0

4

5

3

Open Elective Courses.

Open Elective IV [Communicative English]

3

0

0

3

4

Professional Core Course

Software Engineering

3

0

0

3

5

Project

Project II

0

0

12

6

6

 

Internship

-

-

-

3

 

 

No. of hours

13

0

20

 

33 Hours                                          Total Credits

26

Semester 8

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Project

Project III

0

0

30

15

2

Project

Seminar

-

-

-

3

3

 

Grand Viva

-

-

-

3

3

 

No. of Hours

0

0

30

 

                 30 Hours

21

FACULTY MEMBER

Dr. Susanta Mitra

Pro-Vice Chancellor and Director - School of Engineering & Allied Sciences

Prof. (Dr.) Susanta Mitra has a total experience of more than 33 years covering Academics and IT industries including few renowned multinationals. He did his Ph.D. in Computer Science domain from Jadavpur University, Kolkata. He has active Research interests in emerging areas of technologies and innovative projects. His research interests include Data Science & Analytics, Machine LearningE-learning, IOT and online social networking. He has published several papers and book chapters in International Journals and Conferences. He has prepared a Research Monograph for an International Publisher. He has worked in several International and National IT projects in India and abroad.

Dr. Pranam Paul, Assistant Professor

Mr. Paul has 15 years of teaching and research experience. He did his PhD in Engineering where he specialized in Cryptography and his research areas were primarily Cryptography, Data Security, DBMS, Computer Graphics, Image Processing, LTP, etc. His current research project titles “A Solution towards Big Data Storage and Data management for Efficient Data Handling in Secured File System Based Cloud Environment through Services” is under the process of review in WOS – B, Department of Science and Technology (DST), Govt. of India. He had featured in the “Top 100 Engineers, 2011” and “Outstanding 2000 Intellectuals of the 21st Century, 2012” lists selected by International Biographical Centre, Cambridge, England. He has 11 National and 79 International Publications on his name. He has been to 7 National and 4 International cCnferences organized by various groups.

Dr. Poulami Das, Assistant Professor

Dr. Das has 5 years of teaching and research experience. She did her PhD in CSE and her area of research was Soft Computing. She has had 3 International Publications on her name. Apart from this, she attended 1 National and 5 International Conferences.

Ms. Ruchi Sharma, Teaching Associate

Ms. Sharma has 4 Years of teaching and 6 years of research experience in the area of Software Testing and Software Security & Reliability. She is currently pursuing her PhD in CSE. She has had 10 International Publications and has attended 10 International conferences.

Mr. Bilas Haldar, Teaching Assistant (Lab. Technician)

Mr. Haldar has more than 7 years of teaching and a year of research experience in the fields of Algorithms, Cryptography, AI and Machine Learning. He did his M.Tech. in Software Engineering.

 

EXPERT COMMITTEE: CYBER SECURITY

Dr. Amit Chowdhury

Ex Associate Director-CDAC, Kolkata


EXPERT COMMITTEE: DATA ANALYTICS AND AI&ML

 Prof. Utpal Garain

Professor, ISI Calcutta

 Prof. Aditya Bagchi

Professor, Ramkrishna Vivekananda University, Belur

Mr. Kushal Banerjee

Ex Head, University Relationship, TCS

 

LABORATORY

Computer Science Lab

 

INTERNSHIP & ACHIEVEMENTS

  • Arindam Halder completes his Internship program from CRIS - Centre for Railway Information Systems
  • B.Tech CSE Student of TNU completes her Internship program from IIT, Kanpur
  • Students completes their Internship program from WABCO

 

INDUSTRY PARTNERSHIP

TNU has also collaborated with Batoi Systems Private Limited (BSPL), Bhubaneswar to provide better understanding of Computer Science and Engineering in general and specifically Cyber Security, Internet of Things (IoT), large Data Sciences, etc. other current strengths in CSE to its students. BSPL to provide assistance in drafting the syllabus for B.Tech & M.Tech programme along with help in establishing laboratory and CSE vertical with stress on modern areas including its applications.

CAREER PROSPECTS

Cyber world is facing new challenges every day from hackers and malicious programmers across the globe. Banking, E-commerce, Confidential Industrial Data, Forensic Industries and Defence related data and Employee data of big and small enterprises needs security implementations in place. This specialization remained in demand by government and nongovernment organizations for long time.

Some of the top companies are Mu Sigma, Fractal Analytics, Crayon Data, Latent View, Absolutdata, Global Analytics, IBM, Convergytics.

Data Analytics is creating new jobs and changing existing ones. Data Analytics discipline has got wide acceptance in forecasting, planning and e-commerce enterprises. Data analytics has played a big role in big establishments dealing with huge amounts of information such as hospitals, banks and insurances, prediction of customer behaviour, detect trends, cross-selling, customer relationship management analytics, demand prediction and failure prediction

All the specializations offered through this program have got wide acceptance in industries and enterprises and prepares student for best of practices in respective specialization.

Some of the top companies are Aspirant Infotech Private Limited, CAT CyberLabs, CYBER COPS India, Cyber Octet Pvt. Ltd., Cyberoam Technologies, Delta, Delta Protective Services, etc

 

Get In Touch

  • City Office: Monday - Friday: 11:00 AM - 6:00 PM
  • Saturday (1st, 3rd, 5th) - 11:00 AM - 6:00 PM
  • Campus: Monday - Friday 10AM - 4PM
  • Phone: +91 7605081710 / +91 9163610909 
  • Email: contact@tnu.in

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