5 Year Integrated M.Tech in Computer Science Engineering
An integrated programme that develops deep technical expertise in computing, algorithms and advanced engineering systems for future technology careers.
Programme overview
The five-year integrated B.Tech + M.Tech in computer science & engineering combines undergraduate and postgraduate study into a continuous academic pathway. It is designed to prepare students with both solid foundations in computing and advanced capabilities in specialised and research-oriented aspects of computer science.
Fundamental computing and engineering
Strong grounding in computer science principles, mathematical reasoning and engineering fundamentals.
Advanced technology learning
Exposure to key areas such as algorithms, machine learning, systems and security as part of the integrated master’s component.
Research capability development
Opportunities to engage in project, laboratory and design work that build analytical depth and problem-solving skills.
Preparation for careers and higher study
Integrated depth that supports roles in the software industry, research labs or further academic study.
Programme details
Programme objective
- Graduates will identify and address complex challenges of the future, contributing to the advancement 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.
Programme structure
The integrated structure is organised progressively to build breadth and depth:
- Years 1–2: foundational phase: core courses in mathematics, fundamentals of computing, engineering sciences and introductory computer science.
- Years 3–4: professional phase: advanced computing topics, software and systems engineering, data and algorithm courses aligned with industry needs.
- Year 5: master’s phase: specialised advanced coursework and an integrated research/design project under faculty supervision.
The design ensures continuity between undergraduate breadth and postgraduate depth in computing.
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | MA 1101 | Mathematics-I (Calculus & ODE) | 4 | 1 | 0 | 5 |
| 2 | CH 1101 / CH1103 | Chemistry I + Lab | 2 | 1 | 2 | 4 |
| 3 | EE 1101 | Intro to Electrical Engineering | 2 | 1 | 2 | 2 |
| 4 | EE 1105 | Electronics | 2 | 1 | 2 | 2 |
| 5 | CS 1101 | Introduction to Computing | 2 | 1 | 2 | 4 |
| 6 | HS 1102 | Media Project | 1 | 0 | 2 | 1.5 |
| 7 | HS 1101 | English | 0 | 3 | 0 | 3 |
| 8 | HS 1104 | Intro to Entrepreneurship | 0 | 0 | 3 | 1 |
| 9 | HS 1103 | French – I | 0 | 2 | 0 | 0.5 |
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | MA 1202 | Mathematics-2 (Linear Algebra, Complex Analysis) | 3 | 1 | 0 | 4 |
| 2 | PH 1202 | Physics-I | 2 | 1 | 2 | 4 |
| 3 | BI 1201 | Biology | 3 | 0 | 0 | 3 |
| 4 | CS 1201 | Data Structures | 3 | 1 | 2 | 5 |
| 5 | CS 1202 | Discrete Mathematical Structures | 2 | 0 | 0 | 2 |
| 6 | ME 1202 | Workshop Practice | 0 | 0 | 2 | 1 |
| 7 | CE 1101 | Earth and Environmental Sciences | 2 | 0 | 0 | 2 |
| 8 | HS 1201 | Entrepreneurship Practice | 0 | 0 | 2 | 1 |
| 9 | HS 1202 | Professional Ethics | 0 | 1 | 0 | 1 |
| 10 | HS 1203 | French-II | 0 | 2 | 0 | 0.5 |
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | MA 2103 | Mathematics-3 (Probability & Statistics) | 3 | 1 | 0 | 4 |
| 2 | PH 2102 | Physics-II | 3 | 1 | 2 | 5 |
| 3 | CS 2101 | Optimization Techniques for AI | 3 | 0 | 0 | 3 |
| 4 | CS 2102 | Design and Analysis of Algorithms | 3 | 0 | 2 | 4 |
| 5 | EE 2101 | Signals and Systems | 3 | 1 | 0 | 4 |
| 6 | CS 2104 | Programming Workshop | 0 | 0 | 2 | 0.5 |
| 7 | HS 2101 | Lean Start-up | 0 | 0 | 3 | 1 |
| 8 | HS 2102 | Principle of Economics | 3 | 0 | 0 | 1.5 |
| 9 | HS 2103 | French-III | 0 | 2 | 0 | 0.5 |
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | MA 2208 | Mathematics-4 (Numerical Methods) | 3 | 0 | 2 | 4 |
| 2 | CS 2201 | Digital Logic Design & Computer Architecture | 3 | 1 | 0 | 4 |
| 3 | CS 2202 | Machine Learning | 3 | 0 | 0 | 3 |
| 4 | CS 2102 | Artificial Intelligence | 3 | 0 | 0 | 3 |
| 5 | CS 2204 | Theory of Computation | 3 | 0 | 0 | 3 |
| 6 | CS 2205 | Programming Workshop | 0 | 0 | 2 | 0.5 |
| 7 | HS 2201 | Design Thinking | 1 | 0 | 2 | 2 |
| 8 | HS 2202 | Financial Accounting | 3 | 0 | 0 | 1.5 |
| 9 | HS 2203 | French-IV | 0 | 2 | 0 | 0.5 |
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | CS 3101 | Compiler Design | 3 | 0 | 0 | 3 |
| 2 | CS 3102 | Operating Systems | 3 | 0 | 2 | 4 |
| 3 | CS 3103 | Database Management Systems | 3 | 0 | 2 | 4 |
| 4 | CS 3105 | Object-Oriented Programming | 2 | 0 | 2 | 3 |
| 5 | CS 3106 | Microprocessors and Interfacing | 2 | 0 | 2 | 3 |
| 6 | CS 3107 | Digital Image Processing | 3 | 0 | 0 | 3 |
| 7 | — | Liberal Arts Elective I | 2 | 0 | 0 | 2 |
| 8 | CS 3104 | Programming Workshop | 0 | 0 | 2 | 1 |
| 9 | HS 3102 | French-V (Optional) | 0 | 2 | 0 | 0.5 |
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | CS 3205 | Computer Networks | 3 | 0 | 2 | 4 |
| 2 | CS 3206 | Software Engineering | 2 | 0 | 2 | 3 |
| 3 | CS 3223 | Neural Networks & Deep Learning | 3 | 0 | 0 | 3 |
| 4 | — | Elective I | 3 | 0 | 0 | 3 |
| 5 | — | Elective II | 3 | 0 | 0 | 3 |
| 6 | HS 3201 | Introduction to Professional Development | 2 | 0 | 0 | 2 |
| 7 | — | Liberal Arts Elective II | 2 | 0 | 0 | 2 |
| 8 | HS 3202 | French (Optional) | 0 | 2 | 0 | 0.5 |
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | CS 4101 | Distributed Systems | 3 | 0 | 2 | 4 |
| 2 | CS 4103 | Cryptography & Network Security | 3 | 0 | 0 | 3 |
| 3 | CS 4104 | Computational Intelligence & Evolutionary Computing | 3 | 0 | 0 | 3 |
| 4 | CS 5104 | Mathematics for AI & Data Science | 3 | 0 | 0 | 3 |
| 5 | — | Elective III | 3 | 0 | 0 | 3 |
| 6 | — | Elective IV | 3 | 0 | 0 | 3 |
| 7 | — | Liberal Arts Elective III | 2 | 0 | 0 | 2 |
| 8 | HS 4101 | French – VII (Optional) | 0 | 2 | 0 | 0.5 |
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | CS 5203 | Natural Language Processing | 3 | 0 | 0 | 3 |
| 2 | CS 5202 | Computer Vision | 3 | 0 | 0 | 3 |
| 3 | CS 5209 | Advanced Algorithms | 3 | 0 | 0 | 3 |
| 4 | — | Elective V | 3 | 0 | 0 | 3 |
| 5 | — | Elective VI | 3 | 0 | 0 | 3 |
| 6 | — | Elective VII | 3 | 0 | 0 | 3 |
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | CS 4121 | Computational Sequence Modelling | 3 | 0 | 0 | 3 |
| 2 | CS 4122 | Reinforcement Learning | 3 | 0 | 0 | 3 |
| 3 | — | Elective VIII | 3 | 0 | 0 | 3 |
| 4 | — | Elective IX | 3 | 0 | 0 | 3 |
| 5 | CS 5208 | Dissertation | 0 | 0 | 6 | 6 |
| Sr. No. | Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|---|
| 1 | CS 5301 | Dissertation | 0 | 0 | 18 | 18 |
| Total Credits | 18 | |||||
| Course Code | Elective Title |
|---|---|
| CS3220 | GPU Programming |
| CS3227 | Introduction to Robotics |
| CS3225 | Computational Biology |
| CS3226 | Control Systems |
| CS3224 | Recommender Systems |
| CS4106 | Wireless Sensor Networks |
| CS4107 | Computability and Complexity Theory |
| CS4108 | Quantum Computing and Quantum Machine Learning |
| CS4157 | Deep Learning |
| CS4110 | High Performance Computing |
| CS3201 | Big Data Analytics |
| CS4222 | Social Computing |
| CS4221 | Internet and Society |
| CS4223 | Performance Models of Computing Related Systems |
| CS4224 | Advanced Computer Networks |
| CS4225 | Enterprise Software Architecture |
| CS4187 | Game Theory |
| CS4189 | Medical Image Analysis |
| CS4285 | Foundations of Immersive Technology |
| CS4286 | Foundations of Cybersecurity and Privacy |
| CS4122 | Reinforcement Learning |
| CS4123 | Computational Genomics |
| CS4104 | AI in Industry 4.0 |
FAQs
It is a five-year, full-time integrated degree that awards both a B.Tech and M.Tech in computer science & engineering upon completion.
Yes. The master’s component includes advanced coursework and research or project work under supervision.
The integrated pathway offers a continuous and deeper academic experience, reducing overall duration while building both undergraduate fundamentals and postgraduate specialisation.
Yes. The integrated master’s component positions graduates well for doctoral study in computing and related fields.
Yes. Mahindra University’s engineering programmes, including the integrated degree, follow a fully residential model.
