B.Tech in Computer Science and Engineering With Specialization in Cyber Security/ Data Analytics/ AI & ML
| 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 Learning, E-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
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
