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| Course Offered | Duration (in Years) | Eligibility |
|---|---|---|
| B.TECH IN COMPUTER SCIENCE AND ENGINEERING WITH SPECIALIZATION IN AI & ML | 4 | 12th standard pass with Physics, Maths, Chemistry/ Computer Science with at least 60% marks. |
| B.TECH IN COMPUTER SCIENCE AND ENGINEERING WITH SPECIALIZATION IN AI & ML (Lateral Entry) | 3 | (i) A 3 Years Diploma from an AICTE approved College or UGC recognised University in India with a minimum of 60% marks (ii) A personal interview by the competent authority of the University (iii) Credit transfer possible from other recognised University / College in 3rd / 5th semester with terms & conditions. |
Disclaimer: TNU reserves the right for relaxation in admission criteria for the most deserving candidates.
Engineers are in high demand because they harness the power of AI and ML to provide solutions to applications like 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 Scientist, 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, Embedded Systems, and Industrial IoT is growing day by day and going to provide huge opportunities in employment, research, and entrepreneurship in the near future. Graduates can pursue M.Tech at various Universities / Institutes in the above specializations as the demand in these areas shall keep increasing.
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 | |||||
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 | |||||
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 | |||||
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 | 4 Microprocessor 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 | |||||
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 | |||||
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 | |||||
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 | |||||
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 | |||||
| Semester | Type of Course | Course Title | Hours per Week | Credits | Cumulative Minimum Credits required for Certificate / Diploma / Degree / Honours | ||
| Lecture | Tutorial | Practical | |||||
| I | Mandatory Course | Engineering Mathematics – I | 3 | 0 | 0 | 3 | Certificate in CSE |
| Mandatory Course | Introduction to AI | 4 | 0 | 0 | 4 | ||
| Mandatory Course | Programing for Problem Solving | 2 | 0 | 4 | 4 | ||
| Mandatory Course | Basic Electrical and Electronics Engineering | 2 | 0 | 4 | 4 | ||
| Minor Stream (Elective Paper 1) | Fundamentals of Cyber Security | 4 | 0 | 0 | 4 | ||
| Multidisciplinary (Elective Paper 2) | GE – Paper | 2 | 0 | 0 | 2 | ||
| Ability Enhance Course (Comp 1) | English Language & Personality Development | 1 | 0 | 2 | 2 | ||
| Skill Enhancement Course (Comp 2) | Introduction to Cloud Computing | 1 | 0 | 0 | 1 | ||
| Value Added Course (Comp 3) | Constitution of India (Basic) | 1 | 0 | 0 | 1 | ||
| II | Mandatory Course | Engineering Mathematics-II | 3 | 0 | 0 | 3 | |
| Mandatory Course | Engineering Physics | 3 | 0 | 4 | 5 | ||
| Mandatory Course | Probability and Statistics with R | 2 | 0 | 2 | 3 | ||
| Minor Stream (Elective Paper 1) | Principal of Robotics | 2 | 0 | 4 | 4 | ||
| Multidisciplinary (Elective Paper 2) | GE – Paper | 2 | 0 | 0 | 2 | ||
| Ability Enhance Course (Comp 1) | English Language & Personality Development | 1 | 0 | 2 | 2 | ||
| Value Added Course (Comp 3) | Constitution of India (Advanced) | 1 | 0 | 0 | 1 | ||
| Skill Enhancement Course (Comp 2) | 32 Hrs Workshop on Cloud Data Management along with assesment | 0 | 2 | 0 | 2 | ||
| Grand Total | 34 | 2 | 22 | 47 | |||
| Semester | Type of Course | Course Title | Hours per Week | Credits | Cumulative Minimum Credits required for Certificate / Diploma / Degree / Honours | ||
| Lecture | Tutorial | Practical | |||||
| III | Mandatory Course | Data Structures and Algorithms | 3 | 0 | 4 | 5 | Diploma in CSE |
| Mandatory Course | Programming with Python | 2 | 0 | 4 | 4 | ||
| Mandatory Course | Digital Logic and Microprocessor | 3 | 0 | 0 | 3 | ||
| Mandatory Course | Optimization Techniques | 2 | 0 | 0 | 2 | ||
| Minor Stream (Elective Paper 1) | Cyber-crime Investigations and Forensics | 2 | 0 | 4 | 4 | ||
| Multidisciplinary (Elective Paper 2) | GE – Paper | 2 | 0 | 0 | 2 | ||
| Ability Enhance Course (Comp 1) | English Language & Soft Skills | 1 | 0 | 2 | 2 | ||
| Value Added Course (Comp 3) | Introduction to Climate Change | 1 | 0 | 0 | 1 | ||
| Skill Enhancement Course (Comp 2) | Introduction to Blockchain Technology | 1 | 0 | 0 | 1 | ||
| Summer Internship – 1 | 0 | 0 | 4 | 2 | |||
| IV | Mandatory Course | Design and Analysis of Algorithms | 3 | 0 | 4 | 5 | |
| Mandatory Course | Computer Organisation & Architecture | 3 | 0 | 4 | 5 | ||
| Mandatory Course | Object Oriented Programming | 3 | 0 | 4 | 5 | ||
| Minor Stream (Elective Paper 1) | Embedded Systems and Security | 2 | 0 | 4 | 4 | ||
| Multidisciplinary (Elective Paper 2) | GE – Paper | 2 | 0 | 0 | 2 | ||
| Ability Enhance Course (Comp 1) | English Language & Soft Skills | 1 | 0 | 2 | 2 | ||
| Skill Enhancement Course (Comp 2) | 32 Hrs Workshop on Use of Blockchain using Smart Contracts including Assesments | 0 | 2 | 0 | 2 | ||
| Value Added Course (Comp 3) | Impact of Climate Change and its effect | 1 | 0 | 0 | 1 | ||
| Grand Total | 32 | 2 | 36 | 52 | |||
| Semester | Type of Course | Course Title | Hours per Week | Credits | Cumulative Minimum Credits required for Certificate / Diploma / Degree / Honours | ||
| Lecture | Tutorial | Practical | |||||
| V | Mandatory Course | Database Management System | 3 | 0 | 4 | 5 | Degree in Bachelor of AIML |
| Mandatory Course | Operating System | 3 | 0 | 4 | 5 | ||
| Mandatory Course | Introduction to Machine Learning | 3 | 0 | 4 | 5 | ||
| Minor Stream (Elective Paper 1) | Security & Emerging Technologies | 2 | 0 | 4 | 4 | ||
| Multidisciplinary (Elective Paper 2) | GE – Paper | 2 | 0 | 0 | 2 | ||
| Value Added Course (Comp 3) | Gender Sensitization (Basic) | 1 | 0 | 0 | 1 | ||
| Ability Enhance Course (Comp 1) | English Language & Soft Skills | 1 | 0 | 2 | 2 | ||
| Summer Internship – 2 | 0 | 0 | 6 | 3 | |||
| VI | Mandatory Course | Computer Networks | 3 | 0 | 4 | 5 | |
| Minor Stream (Elective Paper 1) | Cryptography | 2 | 0 | 4 | 4 | ||
| Multidisciplinary (Elective Paper 2) | GE – Paper | 2 | 0 | 0 | 2 | ||
| Ability Enhance Course (Comp 1) | English Language & Soft Skills | 1 | 0 | 2 | 2 | ||
| Value Added Course (Comp 3) | Gender Sensitization (Advanced) | 1 | 0 | 0 | 1 | ||
| Skill Enhancement Course (Comp 2) | 45 Hrs Workshop on IoT for Automation and assesments | 1 | 2 | 0 | 3 | ||
| Grand Total | 25 | 2 | 34 | 44 | |||
| Semester | Type of Course | Course Title | Hours per Week | Credits | Cumulative Minimum Credits required for Certificate / Diploma / Degree / Honours | ||
| Lecture | Tutorial | Practical | |||||
| VII | Mandatory Course | Deep Learning | 3 | 0 | 4 | 5 | Degree in Honours of AIML |
| Mandatory Course | Unsupervised Learning | 3 | 0 | 4 | 5 | ||
| Mandatory Course | Software Engineering | 2 | 0 | 0 | 2 | ||
| Minor Stream (Elective Paper 1) | Application Security & Auditing | 2 | 0 | 4 | 4 | ||
| Summer Internship – 3 | 0 | 0 | 4 | 2 | |||
| VIII | Mandatory Course | Business Analytics | 3 | 0 | 4 | 5 | |
| Mandatory Course | Natural Language Processing | 3 | 0 | 4 | 5 | ||
| Minor Stream (Elective Paper 1) | AI for Robotics | 2 | 0 | 4 | 4 | ||
| Research Project / Dissertation | Project III | 0 | 0 | 24 | 12 | ||
| Assessment | Grand Viva | 0 | 0 | 6 | 3 | ||
| Grand Total | 18 | 0 | 58 | 47 | |||