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B.Tech In Computer Science & Engineering With Specialization In Data Science / Cyber Security / AI & ML / Embedded Systems & Industrial IOT

 

Computer Science College in India

COURSE OFFERED DURATION (IN YEARS) ELIGIBILITY CRITERIA

B.Tech In Computer Science & Engineering With Specialization In Data Science / Cyber Security / AI & ML / Embedded Systems & Industrial IOT

4

12th standard pass with Physics, Maths, Chemistry/ Computer Science with at least 60% marks.

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.


The recent technological advancement occurring around the world revolve round the development of smart and intelligent complex Cyber Physical Systems (CPS) with high speed connectivity for wide range of application areas (Manufacturing and computing, Biomedical, Transportation, Automation, wireless communication, safety monitoring systems, surveillance, renewable energy, defence, aerospace and others). Such cyber physical systems, which involve many embedded sensors and actuators connected with the Internet-of-Things (IoT) along with Data Analytics, Cloud Computing, Block Chain technology is providing technological solution for a wide range of areas. This is indeed an interdisciplinary subject and such CPS based solutions is being envisioned as the technology of the present as well as the future. This has transformed the way systems operate and is the reason of next level Industry 4.0.

A specialization on Embedded Systems and Industrial IoT will definitely make a student ready for the large industry demand in this field. In fact, the Indian government expects the IoT industry is on course to cross $18 billion by 2022. the number of connected devices would be 30 billion by 2022 globally, with India having a share of 5-6 percent of the global IoT industry. The Government of India’s IoT policy aims at building an entire ecosystem around IoT and to incentivise the players in the ecosystem.

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

COURSE STRUCTURE: EMBEDDED SYSTEMS AND INDUSTRIAL IOT

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

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

0

0

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

Engineering Science Course

Analog and Digital Electronics

3

0

2

4

2

Basic Science Course

Mathematics II

3

1

0

4

3

Engineering Science Course

Workshop / Manufacturing Practices

0

0

4

2

4

Engineering Science Course

Programming for Problem Solving

3

1

4

6

5

 

Humanities and Social Sciences including Management

English Communication & Organizational  Behaviour

2

0

2

3

6

Open elective

General  Elective I

3

0

0

3

 

 

No. of hours

14

2

12

 

28 hours    Total Credits

22

Semester 3

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Core Courses

Data Communication

3

0

2

4

2

Professional Core Courses

Data Structure and Algorithms 

3

1

4

6

3

Professional Core Courses

Microprocessor and Microcontroller

3

0

4

5

4

Professional Elective Courses

Python Programing

3

0

4

5

5

Professional Core Courses

Discrete Mathematics

3

1

0

4

 

 

No. of hours

15

2

14

 

31 hours    Total Credits

24

Semester 4

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Core Course

Digital Systems Design

3

0

2

4

2

Professional Core Courses

Computer Architecture for Cyber Physical System

3

0

2

4

3

Professional Core Courses

Operating System

3

0

4

5

4

Professional Core Courses

Object Oriented Programming

3

1

4

6

5

Professional Core Courses

Fundamentals of IoT

3

0

2

4

 

 

No. of hours

15

1

14

 

30 hours    Total Credits

23

  1. MOOCs Course on ‘Software Engineering’ (3-0-0).

NOTE: Students may complete this course during the summer vacation between Sem IV and V. The credit so earned may be transferred to Semester V.

Semester 5

Sl No

Type of Course

 

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

Embedded Linux and RTOS

3

0

3

4.5

2

Professional Core Courses

Design and Analysis of Algorithm

3

0

4

5

3

Professional Core Courses

Database Management System 

3

0

4

5

4

Professional Core Courses

Compiler Design and Automata Theory

4

0

0

4

5

Professional Core Courses

Wireless Sensor Network

3

0

3

4.5

6

Humanities and Social Sciences including Management Course

Engineering Economics

2

0

0

2

7

 MOOCs Course

Software Engg

 

 

 

3

8

 

No. of hours

18

0

14

 

32 hours    Total Credits

28

Semester 6

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Courses

Cloud Computing

3

0

4

5

2

Professional Core Course

Industrial IoT

3

0

4

5

3

Professional Elective Courses

Security Techniques for IoT Systems and Networks

3

0

0

3

4

Professional Elective Courses

Fundamentals of  AI and ML

3

0

4

5

5

Project

Project I

0

0

6

3

 

 

No. of hours

12

0

18

 

30 hours    Total Credits

21

Semester 7

Sl No

Type of Course

Course title

Hours per week

Credits

Lecture

Tutorial

Practical

1

Professional Elective Course

Design of Smart Systems

3

0

0

3

2

Professional Elective Courses

Big Data Analytics with Hadoop / Spark 

3

0

4

5

3

Open Elective Courses.

Gen. Elective II

3

0

0

3

4

Professional Elective Course

Computer Vision

3

0

4

5

5

Project

Project II

0

0

12

6

6

 

Internship

-

-

-

3

 

 

No. of hours

12

0

20

 

32 Hours        Total Credits

25

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 the 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 on 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 Ph.D. 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 titled “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 in his name. He has been to 7 National and 4 International conferences organized by various groups.

Dr. Kalyanashis De, Assistant Professor

Dr. De has been 8 years of teaching and an overall research experience of 9 years in the field of Condensed Matter Physics. He did his Ph.D. in Physics and is currently involved in a project regarding the effect of A-site sophisticated disorder on the Electromagnetic Properties of ‘A-site ordered RBaMn2O6 (R= rare earth)’ perovskite. He has received several rewards and recognition, some of which are Dr. D. S. Kothari Postdoctoral Fellowship by UGC, Postdoctoral Fellowship by FCT, Portugal, and Senior Research Fellowship by Indian Association from the Cultivation of Science, Kolkata. He has 10 International Publications in his name. Dr. De has been the PI of a project granted by UGC-DAE in the CRS scheme for 3 years (2017-19).

Dr. Ayan Chatterjee, Assistant Professor

Dr. Chatterjee has 2 years of teaching experience. He did his Ph.D. in Mathematics and he has overall 5 years of research experience in the areas of Mathematical Modelling of Contaminant Flow in Groundwater, Mathematical Modelling of Surface Water flow, Geo-Mathematical Modelling, and Transport in Porous Media. He has published 8 Research Articles in International Journals (5 SCI and 3 Scopus) and presented 2 articles at International Conference.

Dr. Mostaid Ahmed, Assistant Professor

Dr. Ahmed has 2 years of teaching experience. He did his Ph.D. in Applied Mathematics and his research areas were Solid Mechanics, Theory of Elastic Waves, Geodynamics, and Mathematical Modeling. He has had 11 International Publications to his name and has attended 3 International Conferences as well.

Dr. Manashi Chakraborty, Assistant Professor

Dr. Chakraborty has 13 years of teaching experience and has an overall research experience of 11 years. Currently, she has been working on projects involving Dependence of Exchange Bias on Interparticle Interaction and Improving multiferroicity with RGO/GO/Graphene-based Nanocomposites.  She did her Ph.D. in Chemistry and her areas of research have been Synthetic Inorganic Chemistry, Coordination Chemistry, and Nanomaterials Synthesis, Characterization, and Magnetic Properties Study. She has a National and 5 International Publications in her name.

Dr. Debasis Das, Assistant Professor

Dr. Das has 15 years of teaching experience and an overall research experience of 5 years. He holds a Ph.D. in Engineering with research expertise in material selection in mechanical design, decision making, and soft computing in engineering design, Design optimization. He has 3 research publications in Peer-Reviewed International Journal and 3 National and International Conference Papers to his credit.

Dr. Mushtaq Ahmad, Assistant Professor

Dr. Ahmad has 4 years of teaching experience. He holds a Doctorate in Commerce and his research area was Marketing. He has 12 National and International Publication. He has attended 3 National and 5 International Conferences organized by various groups. 

Dr. Abhishek Ghosh, Assistant Professor

Dr. Ghosh has 6 years of research experience in the adoption & diffusion of innovation and nutrition-sensitive agriculture. He did his Ph.D. in Agricultural Extension and has 4 International Publications. He has attended a National and an International Conference.

Dr. Santanu Ray Chaudhuri, Assistant Professor

Dr. Chaudhuri has 19 years of teaching experience. He has done his Ph.D. in Economics where he specialized in Economic Inequality and Human Capital & Growth. He has 12 years of research experience in Economic Growth, Human Capital & Inequality, Labour Economics, and Environmental Economics as well as 2 years of industry experience. He has had various awards and accolades bestowed upon him like a State Funded Scholarship, selected as a team member in the Capacity Building Project organized by Indian Statistical Institute, Kolkata, Resource Person on ‘Macroeconomics and Public Policy’ at South State Gujarat University, Surat and Resource Person on ‘Illicit Fund Transfer’, Gokhale Institute of Politics and Economics, Pune. He has 7 National and 6 International Publications. He has attended 2 National Conferences.

Dr. Amit Sarkar, Assistant Professor

Dr. Sarkar has 5 years of teaching experience and an overall research experience of 20 years. He did his Ph.D. in Microbiology and his research area was Molecular Genetics of Pathogenic Bacteria. He has 9 International Publications in his name. He has attended 2 International Conferences.

Dr. Poulomi Chakraborty, Assistant Professor

Dr. Chakraborty has been teaching for more than a year now and has an overall research experience of three years in “Exploration of Natural and Synthetic Molecule for the Inhibition of Microbial Biofilm”. She did her Ph.D. in Biotechnology and has ten international publications to her name, to date. Apart from this, she has attended five national and three international seminars organized by various groups.

Mr. Subrata Routh, Faculty

Mr. Routh has 20 years of global experience in academics and industry. He did his MBA in Hotel Management. He has experience working with many international hotels such as Hotel Intercontinental, Ritz Carlton, Bahrain, and more. 

Dr. Debobani Biswas, Assistant Professor

Dr. Biswas has been teaching for twenty years and has a collective research experience of eight years. She did her Ph.D. in English Literature and her research area was “African American Drama”. To date, she has had two international and 1 National Publication to her name. Apart from this, she has attended 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 Ph.D. in CSE. She has had 10 International Publications and has attended 10 International conferences.

Mr. Jaydeb Mondal, Teaching Associate

Mr. Mondal has been teaching for the last two years and has an overall research experience of seven years. He did his MTech. in CSE and his area of research was “Image and Video Processing” and “Machine Learning”. Also, he was awarded the TCS Research Scholarship. To date, he has had two international publications and has attended an international conference as well.

Dr. Srijani Banerjee, Faculty (Visiting)

Dr. Banerjee has 3 years of teaching and an overall 5 years of industry experience. She did her Post-Graduation (MPT) with a specialization in Cardiothoracic Disorders and ICU Management. She is also a member of the Indian Association of Physiotherapy. Her interest areas are Geriatric Care, Dementia, and Mental Health.

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. Now He is doing Ph.D.

EXPERT COMMITTEE: CYBER SECURITY

Dr. Amit Chaudhuri

Former Associate Director-CDAC, Kolkata


EXPERT COMMITTEE: DATA ANALYTICS AND AI&ML

Prof. Utpal Garain (Honorary Member)

Professor, ISI Calcutta

Prof. Aditya Bagchi

Professor, Ramkrishna Vivekananda University, Belur

Mr. Kushal Banerjee

Former Head, University Relationship, TCS

 

EXPERT COMMITTEE: EMBEDDED SYSTEMS AND INDUSTRIAL IOT

Dr. Hena Ray, Joint Director, CDAC, Kolkata

Dr. Amlan Chakraborty, Professor, CSE,  University of Calcutta

LABORATORY

Computer Science Lab

Computer lab with software like Kali Linus, VMWare, Open IAM, Vulnerability scanners, NsLookUP, R, Oracle , Hadoop, Sikuli are provided.

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

According to a research Indian IoT market comprising Industrial IoT and consumer IoT is projected to grow at a CAGR of 28.2% during the period 2016-22. As per reports from sources the Indian IoT market is expected to go upto USD 15Bn in 2021. This include the areas of Smart Cities, Smart Factories, Data Driven Healthcare, Artificial Intelligence, Smart retail, Edge computing, Fitness, Smart Agriculture, Fitness etc. Being an interdisciplinary specialization, the fresh graduates will have a wide range of area in which they would be capable of working. This areas include Consumer IoT ( Lifestyle products, Health & fitness monitoring , Home automation, connected homes and buildings) to Industrial IoT ( Smart Cities, Healthcare, Industrial Automation, Retail Automation, Automotive Industry etc) with over 120 firms offering such solutions. Apart from this being a B.Tech in Computer Science with exposure to subjects from upcoming areas like Data Science, AI/ML, Cloud Computing the students will be also able to work in the reputed IT companies. Students may also choose the option of higher studies and the course curriculum is prepared in a manner to fuel them to achieve their goals. There can also be good scope of Entrepreneurship opportunities.

 

Get In Touch

  • Head Office:
  • Mon - Fri: 11:00 AM - 6:00 PM
  • Saturday (1st and 3rd): 11:00 AM - 6:00 PM
  • Phone No.: +91 7044446999
  • The Campus:
  • Mon - Fri: 10:00 AM - 4:00 PM
  • Phone No.: +91 7044446888
  • Email: contact@tnu.in

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