M.Tech in Computer Science Engineering

Highlights of the Program:

The two-year MTech program in CSE at the Indian Institute of Technology Dharwad is proposed to

  1. provide students with a deep understanding of theoretical foundations and advanced concepts in computer science.
  2. 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.
  3. 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.
  4.  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. 

  1. 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.
  2. 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 CategoryCredits
1Institute Core (IC)68 
2Program Core (PC)21
3Elective (E)36

Total:

125

 

  1. Out of 36 credits of elective courses,
    1. 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.
    2. 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).
  2. A mandatory seminar course (4 credits) and 64 credits worth MTP I and MTP II (32 credits each) fall under institute core.
  3. 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:


Year 1: I Semester – Total credits 27-29

S. No.Course NameL-T-P-C / Total CreditsObjective of the CourseCourse Category
1Advanced 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
2Advanced Data Structures and Algorithms Lab0-0-3-3PC
3Combinatorics and Probability3-0-0-6

To provide the foundations of combinatorics and probability theory that are fundamental to CSE discipline

PC
4Advanced Software Development Laboratory1-0-4-6

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
5Elective-16-8


Students choose post-graduate level courses according to their interest of specialization or based on their interest.
Note: Elecective-1 should be relevant to Computer Science and Engineering.

IC
6Communications skillsPP/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 NameL-T-P-C / Total CreditsObjective of the CourseCourse Category
1
Elective-2
6-8

Students choose post-graduate level courses according to their interest of specialization or based on their interest. 


Note: Total credits for Elective is 36. In that at least 24 credits should come from the courses specific to the CSE discipline. 

E
2
Elective-3
6-8E
3
Elective-4
6-8E
4
Elective-5
6E
5
Elective-6
6E
6Seminar0-0-4-4 IC

 

Year 2: III Semester – Total credits 32

S. No.Course NameL-T-P-C / Total CreditsObjective of the CourseCourse Category
1MTech Technical Project – I0-0-32-32First 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 NameL-T-P-C / Total CreditsObjective of the CourseCourse 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 Science3-0-0-6
CS 426        Introduction to Blockchains3-0-0-6
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 Linguistics3-0-0-6
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 Applications3-0-0-6
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