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

 

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

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. Currently, B.Tech Computer Science Engineering is one of the top courses in India that attract lakhs of students every year. B.Tech Computer Science and Engineering at The Neotia University (TNU) is designed with specializations in several important and emerging areas such as, Cyber Security, Data Science, Artificial Intelligence (AI) and Machine Learning (ML) that will help students to gain knowledge and become industry ready for jobs in top Corporates. The curriculum structure is design by the academicians from Indian Statistical Institute (ISI), Jadavpur University, University of Calcutta and industrial experts from Tata Consultancy Services (TCS), Centre for Development of Advanced Computing (CDAC). The state-of-the-art Computer Labs are well equipped with advanced software. Internship and Industrial visit is part of the Curriculum. Students are encouraged to publish journals and articles regularly on National and International platforms.

Specialization in Cyber Security

Cyber Security, also referred to as IT security, emphasizes safeguarding computers, programs, networks, and data from unlicensed or spontaneous access. The cyberworld is facing new challenges every day from hackers and malicious programmers across the globe. Banking, E-commerce, Confidential Industrial Data, Forensic Industries, and Defense-related data, and Employee data of big and small enterprises need security implementations in place. The frequency and intensity of cyber scams and crimes have increased over the last decade, resulting in huge losses for businesses. As incidents of cybercrimes increased significantly, businesses worldwide channeled their spending on advanced information security technologies to strengthen their in-house security infrastructure.

Specialization in Data Science

Data Science is an advanced technology, which demands coding, mathematics, statistics, and some the skills such as machine learning, data mining, and visualization. Data scientists are professionals who can simplify big data through coding and algorithms and turn it into a problem-solving solution for the business. Data scientists operate between the business and IT worlds and drive industries by analyzing complex datasets to tease out insights that companies can leverage into actions. With rising investment in research and development, technological advances are occurring rapidly.

Specialization in Artificial Intelligence & Machine Learning (AI & ML)

AI has now penetrated all the horizons of the service sector. There is rarely any field that is untouched by Artificial Intelligence and it is the life force behind ground-breaking digital technologies and innovations. This specialization is designed to enable students to build intelligent machines, software, or applications with a cutting-edge combination of machine learning and visualization technologies.

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 SCIENCE

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 Science

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

 

 

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

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 Science

[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. Partha Mukherjee, HoD

Dr. Mukherjee has been teaching for the last four years and has an overall industry experience of twenty-four years. He has a research experience of about fifteen years and has done his Ph.D. in Multimedia Database Management System and Data Streaming for Data Analytics. He holds various certifications such as PMP, Lead Auditor Certificate on BS 7799, Certificate on Requirements Management with Rational Requisite Pro, etc. Currently, he has 7 National and 3 International publications to his name. He has been to 9 International Conferences organized by various forums.

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.

Prof. Suman Haldar, Associate Professor

Prof. Haldar has been teaching for fifteen years now. He has research experience of six years in Electric vehicles, IoT and Wireless communication. He is currently pursuing his Ph.D. in ECE and has earlier completed his MTech., B.Tech. and Diploma on the same. To date, he has five national and four international publications to his name.

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

Mr. Asok Bandyopadhyay

Associate Director -  ICT and Services Group

CDAC, Kolkata

Dr. Amlan Chakrabarti

Professor and Director – AKCSIT, University of Calcutta


EXPERT COMMITTEE: DATA ANALYTICS AND AI & ML

Dr. Pradip Kumar Das

Ex-Professor, Jadavpur University

 

Mr. Sourabh Mukherjee

Vice President – Data and Artificial Intelligence Group, Accenture

Dr. Aditya Bagchi

Ex-Professor and Dean, Indian Statistical Institute

 

Dr. Amlan Chakrabarti

Professor and Director – AKCSIT, 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

Specialization in Cyber Security

Cyber Security is one of the fastest-growing industries, and cybersecurity skills are in high demand across different verticals. Once students have the education and qualifications, the jobs are waiting - now and in the future. After completion of the Computer Science & Engineering with specialization in Cyber Security course, students will be able to work as an information security officer, forensic computer analyst, information security analyst, security architect, security engineering security systems administrators, and IT security.

Specialization in Data Science

Data Science is a highly flexible discipline finding its way into all industries. Data science without any doubt is one of the 21st century’s most challenging careers. Important applications of Data Science are in Healthcare, Banking, Manufacturing, E-commerce, Fraud and Risk Detection, Image and Speech Recognition, and Education. The demand for data scientists and their salaries have been growing particularly for a decade. Data Scientist, Data Engineer, Data Architect, Data Administrator, Data Analyst, Business Analyst, Data / Analytics Manager, Business Intelligence Manager are among the prominent Data Scientist job titles. Entrepreneurship can also be a good career option for the pass outs.

Specialization in Artificial Intelligence & Machine Learning (AI & ML)

Engineers are in high demand because they harness the power of AI and ML to provide solutions to applications like a diagnosis of diseases, image processing, real-time personalization, speech recognition, fraud detection, and many more. Students have ample job opportunities in this field. Some demanding job positions include Machine Learning Engineer, Data Scientist, Business Intelligence Developer, Research Scientists, AI engineer, and Robotics Scientist. Entrepreneurship can also be a good career option for graduates.

The importance of B.Tech in Computer Science and Engineering with specialization in Cyber Security, Data Science, Artificial Intelligence and Machine Learning is growing day by day and going to provide huge opportunities in employment, research, and entrepreneurship in near future. Graduates can pursue M.Tech at various Universities / Institutes in the above specializations as the demand in these areas shall keep increasing.

 

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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