myIIT
Highlights of the Program:
The two-year MTech program in CSE at the Indian Institute of Technology Dharwad is proposed to
- provide students with a deep understanding of theoretical foundations and advanced concepts in computer science.
- foster a research-oriented mindset, encouraging students to engage in cutting-edge projects and develop critical thinking skills for addressing complex challenges in the field.
- equip graduates with practical, industry-relevant skills, ensuring they are well-prepared for professional roles and emphasizing ethical considerations in the design and implementation of computer science solutions.
- cultivate a global perspective, instill lifelong learning habits, and develop leadership and teamwork skills, positioning graduates to contribute to the evolving landscape of computer science on a global scale.
Programme and Credit Structure:
In the first year, students will have to take courses and the second year will consist of MTech project (MTP) I and MTP II.
- The minimum number of overall credits required to be completed is 125, out of which 61 credits will be fulfilled using course work, and 64 credits using the MTech project.
- The overall credits would be divided into three categories of courses: (i) Institute Core (IC) courses (68 credits), (ii) Program Core (PC) courses (21 credits) and (iii) Electives (36 credits)
| S. No. | Course Category | Credits |
| 1 | Institute Core (IC) | 68 |
| 2 | Program Core (PC) | 21 |
| 3 | Elective (E) | 36 |
Total: | 125 | |
- Out of 36 credits of elective courses,
- Students should complete at least 24 credits from the elective courses related to CSE discipline (refer Annexure 1). Students are permitted to fulfill their remaining 12 credits either from the elective courses outside the CSE discipline, provided that these courses are at the graduate level (600 or above) or from elective courses related to CSE discipline.
- Students may opt to fulfill their elective credit requirements by enrolling in a maximum of 12 credits of undergraduate (UG) level courses, with the approval of faculty advisor (FA).
- A mandatory seminar course (4 credits) and 64 credits worth MTP I and MTP II (32 credits each) fall under institute core.
- The MTech project starts from the summer following the first year and extends to the third and fourth semesters. The student would be allotted a guide to work on the MTech project before the end of the second semester. There will be a committee to monitor the progress of the students in the project each semester and accord a grade for the project.
Semester-wise Course and Credits Distribution:
| ||||
| S. No. | Course Name | L-T-P-C / Total Credits | Objective of the Course | Course Category |
| 1 | Advanced Data Structures and Algorithms | 3-0-0-6 | To provide the foundations of the practical implementation and usage of algorithms and data Structures. One of the objectives is to ensure that the student evolves into a competent programmer capable of designing and analyzing implementations of algorithms and data structures for different kinds of problems. Another objective is to expose the student to the algorithm analysis techniques, to the theory of reductions, and to the classification of problems into complexity classes. | PC |
| 2 | Advanced Data Structures and Algorithms Lab | 0-0-3-3 | PC | |
| 3 | Combinatorics and Probability | 3-0-0-6 | To provide the foundations of combinatorics and probability theory that are fundamental to CSE discipline | PC |
| 4 | Advanced Software Development Laboratory | 1-2-0-6 | To teach students, advanced problem solving through programming. It aims to train students in writing efficient programs for the problem in different areas of CSE such as software engineering, operating system, networks, computer architecture, databases etc. | E |
| 5 | Elective-1 | 6-8 |
| IC |
| 6 | Communications skills | PP/NP | ||
Year 1: II Semester – 32-34 (Depending on the number of elective credits completed in the previous semester. Overall total credit of 36 for elective to be completed.) | ||||
| S. No. | Course Name | L-T-P-C / Total Credits | Objective of the Course | Course Category |
| 1 | Elective-2 | 6-8 | Students choose post-graduate level courses according to their interest of specialization or based on their interest.
| E |
| 2 | Elective-3 | 6-8 | E | |
| 3 | Elective-4 | 6-8 | E | |
| 4 | Elective-5 | 6 | E | |
| 5 | Elective-6 | 6 | E | |
| 6 | Seminar | 0-0-4-4 | IC | |
Year 2: III Semester – Total credits 32 | ||||
| S. No. | Course Name | L-T-P-C / Total Credits | Objective of the Course | Course Category |
| 1 | MTech Technical Project – I | 0-0-32-32 | First phase of the year-long project. Project work starts from the summer following the first year. The student would be allotted a guide to work on the MTech project before the end of the second semester. There will be a committee to monitor the progress of the student in the project each semester and accord a grade for the project. | IC |
Year 2: IV Semester – Total credits 32 | ||||
| S. No. | Course Name | L-T-P-C / Total Credits | Objective of the Course | Course Category |
| 1 | MTech Technical Project – II | 0-0-32-32 | Second phase of the year-long project. Project work continues from III semester. following the first year. There will be a committee to monitor the progress of the student in the project each semester and accord a grade for the project. | IC |
Annexure-1
The following Table shows the electives related to the CSE discipline.
Course Code | Course | L-T-P-C |
| CS 402 | Distributed Systems | 3-0-0-6 |
| CS 403 | Graph Theory and Combinatorics | 3-0-0-6 |
| CS 410 | Parallel Computing | 3-0-0-6 |
| CS 421 | Logic for Computer Science | 3-0-0-6 |
| CS 426 | Introduction to Blockchains | 3-0-0-6 |
| CS 427 | Mathematics for Data Science | 3-0-0-6 |
| CS 438 | Natural Language Processing | 3-0-0-6 |
| CS 439 | Introduction to Sanskrit Computational Linguistics | 3-0-0-6 |
| CS 601 | Software Development for Scientific Computing | 3-0-0-6 |
| CS 603 | Approximation algorithms | 3-0-0-6 |
| CS 604 | Parameterized Algorithms and Complexity | 3-0-0-6 |
| CS 606 | Advanced Topics in Embedded Computing | 3-0-0-6 |
| CS 607 | Advanced Computer Networks | 3-0-0-6 |
| CS 608 | FPGA for communication networks prototyping | 3-0-0-6 |
| CS 609 | Software Defined Networking and Network Function Virtualization | 3-0-0-6 |
| CS 610 | Advanced Distributed Systems | 3-0-0-6 |
| CS 612 | Statistical Pattern Recognition Laboratory | 0-0-3-3 |
| CS 616 | Statistical Pattern Recognition | 3-0-0-6 |
| CS 621 | Logic and Applications | 3-0-0-6 |
| CS 622 | Special Topics in Automata and Logics | 3-0-0-6 |
| CS 624 | Compilers - Principles and Implementation | 3-0-0-6 |
| CS 810 | Advanced Computer Architecture | 3-0-3-9 |
| EE 606 | Pattern Recognition and Machine learning (PRML) | 3-0-0-6 |
EE 612 | Pattern Recognition and Machine learning (PRML) Laboratory | 0-0-3-3 |
| EE 620 | Neural networks and deep learning (NNDL) | 3-0-0-6 |
| EE 611 | Neural networks and deep learning (NNDL) Laboratory | 0-0-3-3 |