School of Engineering and Technology
M.Tech. in Computer Science and Engineering
Programme Details
Course at a Glance
Credits
76
Semesters
4 Semesters
Specialisations
CSE
Seats
15
School
Engineering and Technology
Programme Structure
Semester I
Total contact hours per week: 23. Credits earned in Semester I: 18.
L denotes lecture hours per week, T tutorial hours per week and P practical hours per week. MSE denotes the mid semester examination, Att attendance, CA teacher continuous assessment, IA internal
assessment and ESE end semester examination.
| Sl. | Course Code | Course Title | Category | L | T | P | Credits |
|---|---|---|---|---|---|---|---|
| 1 | MCS-101 | Advanced Data Structures and Algorithms | PCC | 3 | 0 | 0 | 3 |
| 2 | MCS-102 | Data Science | PCC | 3 | 0 | 0 | 3 |
| 3 | MCS-103 |
Mathematical Foundations for Computer Science |
FC | 3 | 0 | 0 | 3 |
| 4 | MCS-104 |
Research Methodology and Intellectual Property Rights |
RMC | 3 | 0 | 0 | 3 |
| 5 | MCS-105 | Advanced Database Management Systems | PCC | 3 | 0 | 0 | 3 |
| 6 | MCS-151 |
Advanced Data Structures and Algorithms Laboratory |
PCL | 0 | 0 | 2 | 1 |
| 7 | MCS-152 | Data Science Laboratory | PCL | 0 | 0 | 2 | 1 |
| 8 | MCS-171 | Seminar I | SEM | 0 | 0 | 2 | 1 |
| 9 | MCS-181 | Scientific Writing I | AUD | 2 | 0 | 0 | Audit |
| Total | 17 | 0 | 06 | 18 |
Semester II
Total contact hours per week: 23. Credits earned in Semester II: 18. Cumulative credits at the end of Semester II: 36
L denotes lecture hours per week, T tutorial hours per week and P practical hours per week. MSE denotes the mid semester examination, Att attendance, CA teacher continuous assessment, IA internal
assessment and ESE end semester examination.
| Sl. | Course Code | Course Title | Category | L | T | P | Credits |
|---|---|---|---|---|---|---|---|
| 1 | MCS-201 | Advanced Machine Learning Techniques | PCC | 3 | 0 | 0 | 3 |
| 2 | MCS-202 | Advanced Software Engineering | PCC | 3 | 0 | 0 | 3 |
| 3 | MCS-203 | Advanced Computer Networks | PCC | 3 | 0 | 0 | 3 |
| 4 | MCS-21X | Programme Elective I | PEC | 3 | 0 | 0 | 3 |
| 5 | MCS-22X | Programme Elective II | PEC | 3 | 0 | 0 | 3 |
| 6 | MCS-251 |
Advanced Machine Learning Techniques Laboratory |
PCL | 0 | 0 | 2 | 1 |
| 7 | MCS-253 | Advanced Computer Networks Laboratory | PCL | 0 | 0 | 2 | 1 |
| 8 | MCS-271 | Seminar II | SEM | 0 | 0 | 2 | 1 |
| 9 | MCS-281 | Scientific Writing II | AUD | 2 | 0 | 0 | Audit |
| Total | 17 | 0 | 06 | 18 |
Semester III
Total contact hours per week: 34. Credits earned in Semester III: 20. Cumulative credits at the end of Semester III: 56.
L denotes lecture hours per week, T tutorial hours per week and P practical hours per week. MSE denotes the mid semester examination, Att attendance, CA teacher continuous assessment, IA internal
assessment and ESE end semester examination.
| Sl. | Course Code | Course Title | Category | L | T | P | Credits |
|---|---|---|---|---|---|---|---|
| 1 | MCS-31X | Programme Elective III | PEC | 3 | 0 | 0 | 3 |
| 2 | MCS-32X | Programme Elective IV | PEC | 3 | 0 | 0 | 3 |
| 3 | MCS-371 | Seminar III | SEM | 0 | 0 | 12 | 6 |
| 4 | MCS-391 | Dissertation Phase I | DIS | 0 | 0 | 16 | 8 |
| Total | 06 | 0 | 28 | 20 |
Semester IV
Total contact hours per week: 40. Credits earned in Semester IV: 20. Cumulative credits at the end of the Programme: 76
L denotes lecture hours per week, T tutorial hours per week and P practical hours per week. MSE denotes the mid semester examination, Att attendance, CA teacher continuous assessment, IA internal
assessment and ESE end semester examination.
| Sl. | Course Code | Course Title | Category | L | T | P | Credits |
|---|---|---|---|---|---|---|---|
| 1 | MCS-491 | Dissertation Phase II | DIS | 0 | 0 | 40 | 20 |
| Total | 0 | 0 | 40 | 20 |
Consolidated Credit Summary
Audit courses: Scientific Writing I in Semester I and Scientific Writing II in Semester II, each carrying no credit. Bridge courses,
where applicable, carry no credit.
| Semester | PCC | PCL | PEC | FC and RMC |
SEM | DIS | Total |
|---|---|---|---|---|---|---|---|
| I | 09 | 02 | 00 | 06 | 01 | 00 | 18 |
| II | 09 | 02 | 06 | 00 | 01 | 00 | 18 |
| III | 00 | 00 | 06 | 00 | 06 | 08 | 20 |
| IV | 00 | 00 | 00 | 00 | 00 | 20 | 20 |
| Total | 18 | 04 | 12 | 06 | 08 | 28 | 76 |
Programme Electives
A candidate shall choose four Programme Electives in all, two in the second semester and two in the third
semester. The electives are organised into five tracks. A candidate is advised, though not required, to select
at least three of the four electives from a single track so as to develop depth in one area, and may in that case
have the track recorded on the transcript as an area of concentration.
The Department shall notify before the commencement of each semester the electives actually to be offered
in that semester, having regard to the availability of faculty and the registration threshold prescribed in Clause
10.4. Every Programme Elective carries three credits with a lecture, tutorial and practical distribution of 3-0-
0.
Track I: Artificial Intelligence and Machine Learning
| Course Code | Course Title | Offered in | Credits |
|---|---|---|---|
| MCS-211 | Deep Learning and Neural Architectures | Semester II | 3 |
| MCS-212 | Natural Language Processing | Semester II | 3 |
| MCS-213 | Computer Vision and Image Understanding | Semester II | 3 |
| MCS-311 | Reinforcement Learning | Semester III | 3 |
| MCS-312 | Generative Artificial Intelligence and Large Language Models | Semester III | 3 |
| MCS-313 | Explainable and Responsible Artificial Intelligence | Semester III | 3 |
Track II: Data Science and Analytics
| Course Code | Course Title | Offered in | Credits |
|---|---|---|---|
| MCS-221 | Big Data Analytics and Distributed Data Processing | Semester II | 3 |
| MCS-222 | Data Warehousing and Data Mining | Semester II | 3 |
| MCS-223 | Statistical Learning and Predictive Analytics | Semester II | 3 |
| MCS-321 | Information Retrieval and Recommender Systems | Semester III | 3 |
| MCS-322 | Time Series Analysis and Forecasting | Semester III | 3 |
| MCS-323 | Data Visualisation and Storytelling with Data | Semester III | 3 |
Track III: Cyber Security and Privacy
| Course Code | Course Title | Offered in | Credits |
|---|---|---|---|
| MCS-214 | Cryptography and Network Security | Semester II | 3 |
| MCS-215 | Secure Software Design and Application Security | Semester II | 3 |
| MCS-216 | Blockchain Technologies and Distributed Ledgers | Semester II | 3 |
| MCS-314 | Cyber Forensics and Incident Response | Semester III | 3 |
| MCS-315 | Privacy Preserving Computation and Federated Learning | Semester III | 3 |
| MCS-316 | Hardware and Internet of Things Security | Semester III | 3 |
Track IV: Cloud, Distributed and High Performance Computing
| Course Code | Course Title | Offered in | Credits |
|---|---|---|---|
| MCS-224 | Cloud Computing and Virtualisation | Semester II | 3 |
| MCS-225 | Distributed Systems and Consensus | Semester II | 3 |
| MCS-226 | Advanced Operating Systems | Semester II | 3 |
| MCS-324 | High Performance and Parallel Computing | Semester III | 3 |
| MCS-325 | Edge and Fog Computing | Semester III | 3 |
| MCS-326 | DevOps, Containerisation and Site Reliability Engineering | Semester III | 3 |
Track V: Emerging and Interdisciplinary Computing
| Course Code | Course Title | Offered in | Credits |
|---|---|---|---|
| MCS-217 | Internet of Things and Cyber Physical Systems | Semester II | 3 |
| MCS-218 | Soft Computing and Evolutionary Optimisation | Semester II | 3 |
| MCS-219 | Digital Twin and Industrial Intelligence | Semester II | 3 |
| MCS-317 | Quantum Computing and Quantum Algorithms | Semester III | 3 |
| MCS-318 | Augmented Reality, Virtual Reality and Human Computer Interaction | Semester III | 3 |
| MCS-319 | Robotics, Autonomous Systems and Embedded Intelligence | Semester III | 3 |
Audit courses
The Department may additionally notify audit courses on Constitution of India, Value Education, Disaster
Management, Stress and Wellbeing Management, Entrepreneurship and Innovation, and Pedagogy in Higher
Education, which a candidate may take under Clause 17.3.
| Course Code | Course Title | Offered in | Credits |
|---|---|---|---|
| MCS-181 | Scientific Writing I: Technical Reading, Literature Survey and Report Writing | Semester I | Nil |
| MCS-281 | Scientific Writing II: Research Paper Writing, Referencing and Publication Ethics | Semester II | Nil |
Contact Hours and Credit Conversion
| Component | Hours per Week | Credits |
|---|---|---|
| Lecture (L) | 1 | 1 |
| Tutorial (T) | 1 | 1 |
| Practical or Laboratory (P) | 2 | 1 |
| Seminar | 2 | 1 |
| Dissertation | 2 | 1 |