B.Tech in Computer Science Engineering
A 4-year undergraduate program developing computer scientists through a curriculum focused on real-world problem-solving, and industry collaboration.
B.Tech in computer science overview
Our programme builds expertise beyond just coding. The curriculum is structured to give students deep knowledge of computational theory and software design, ensuring they graduate as innovators who can architect complex digital solutions. Students experience:
Foundational mastery
of algorithms, data structures, and computational theory for programming excellence
Hands-on development
with coding labs, software projects, and building full-stack applications
Cutting-edge specialisations
in AI, Cybersecurity, and Data Science through advanced electives and research
Industry-aligned innovation
via hackathons, capstone projects, and internships solving real-world problems
Programme details
Programme objective
- Graduates will be able to identify and solve complex problems of the future and contribute to advancing the frontiers of computer science.
- Graduates will develop original ideas and build technology-driven solutions that simplify processes and improve quality of life.
- Graduates will demonstrate entrepreneurial thinking and advance their careers through continuous development of professional, communication and analytical skills.
Academic structure
Our academic structure is designed to establish robust foundations, followed by increasing specialization in later years.
- Duration: 4 years / 8 semesters
- Total credits & degree requirement: The programme requires not less than 165 credits to be awarded a B.Tech degree.
| Course | L-T-P | Credits |
|---|---|---|
| Math I – Calculus & ODE | 4-1-0 | 5 |
| Earth and Environmental Sciences | 2-0-0 | 2 |
| Fundamentals of Drawing & Practice | 0-0-4 | 2 |
| Introduction to Computer Science | 2-1-2 | 4 |
| Learning to Learn | 1-0-2 | 2 |
| Photography I: Still and Moving Images | 1-0-4 | 3 |
| Introduction to Media and Communication | 1-0-2 | 2 |
| French I | 0-2-0 | 0.5 |
| Course | L-T-P | Credits |
|---|---|---|
| Mathematics – II | 3-1-0 | 4 |
| Physics – I | 2-1-2 | 4 |
| Chemistry – II | 2-0-2 | 3 |
| Electronics | 2-1-2 | 4 |
| Introduction to Computer Science | 2-1-2 | 4 |
| Workshop Practice | 0-0-2 | 0 |
| Introduction to Enterprises & Economy | 2-1-0 | 3 |
| Professional Ethics | 0-1-0 | 1 |
| French Language & Culture – II | 0-2-0 | 0 |
| Course | L-T-P | Credits |
|---|---|---|
| Probability & Statistics | 3-1-0 | 4 |
| Optimization Techniques for AI | 3-0-0 | 3 |
| Signals & Systems | 3-1-0 | 4 |
| Design & Analysis of Algorithms | 2-1-2 | 4 |
| Lean Start-up | 1-0-0 | 1 |
| Principles of Economics | 3-0-0 | 1.5 |
| French – III | 0-2-0 | 0.5 |
| Course | L-T-P | Credits |
|---|---|---|
| Machine Learning with Python | 3-0-2 | 4 |
| Artificial & Computational Intelligence | 2-1-2 | 4 |
| Theory of Computation | 3-0-0 | 3 |
| Digital Logic & Computer Architecture | 3-1-0 | 4 |
| Financial Accounting | 3-0-0 | 1.5 |
| Course | L-T-P | Credits |
|---|---|---|
| Design & Analysis of Algorithms | 2-1-2 | 4 |
| DBMS | 3-0-2 | 4 |
| Operating Systems | 3-0-2 | 4 |
| Microprocessors & Interfacing | – | 3 |
| Object Oriented Programming | – | 3 |
| Course | L-T-P | Credits |
|---|---|---|
| Big Data Analytics | – | 3 |
| Computer Networks | – | 3 |
| Software Engineering | – | 3 |
| High Performance Computing | – | 3 |
| Professional Development & Employability Skills | – | 2 |
| Course | L-T-P | Credits |
|---|---|---|
| Distributed Systems | – | 3 |
| Compiler Design | – | 3 |
| Cryptography & Network Security | – | 3 |
| Elective I | – | 3 |
| Elective II | – | 3 |
| Course | L-T-P | Credits |
|---|---|---|
| Advanced Electives | – | 3–4 |
| Final Year Project | – | 6+ |
| French Language & Culture (Optional) | 0-2-0 | 0 |
FAQs
The CSE curriculum is designed around 11 core departmental courses (40 credits) covering algorithms, data structures, databases, cryptography, and machine learning. It blends strong theoretical grounding with application-driven labs and projects, ensuring graduates are industry-ready from day one.
Students can pursue five professional and open electives (15 credits) in areas like High-Performance Computing, Data Mining, Information Security, Graphics, and Embedded Systems, allowing them to tailor their expertise toward emerging technologies.
The CSE programme encourages research from the undergraduate level, with faculty-mentored projects, capstone work, and access to research labs in AI, Robotics, and Computational Systems. Students are guided by Ph.D. faculty from top global institutions.
With a 12:1 student-faculty ratio, fully residential campus, and project-based learning culture, CSE students experience personalized mentorship, vibrant peer learning, and a collaborative atmosphere ideal for growth and innovation.
