M.Tech. in Communication Systems and Machine Learning (CS&ML)
Program Overview | Semester-wise Program Structure | Admission Process
Program Overview
Master of Technology in Communication Systems and Machine Learning (CS&ML) is a full-time two-year (four semesters) program. The M.Tech. (CS&ML) program is jointly offered by DA-IICT and CR Rao AIMSCS. The program has been specially designed to meet the increasing need for the professionals who would be able to respond to the convergence between communication systems and machine learning.
This program is designed with following objectives:
- To educate and train the students who can contribute to advanced communication systems (including 5G and next generation wireless systems), the advanced machine learning technologies and the confluence of these two.
- To develop research projects on communication systems and machine learning in collaboration with the industry and R&D organizations.
- To apply machine learning techniques in communication systems and beyond.
Apart from courses, students are required to pursue one full year (third and fourth semesters) of research under the guidance of a faculty advisor and submit a master’s thesis in order to obtain the degree of M.Tech. (CS&ML). On successful completion of the program, the students will be able to acquire essential technical and practical knowledge for solving real-world problems in the CS&ML domain using modern technologies and tools, and will have the ability to demonstrate excellent analytical and logical problem-solving skills.
The curriculum mandates a minimum of 61 credits, 40 earned through coursework and 21 credits earned through thesis and internships. Out of the 40 required coursework credits, 24 credits are allocated to compulsory (core) courses, 16 credits are allocated to electives.
Semester-wise Program Structure
(L-lecture, T-tutorial, P-practical, C-credit)
Program Structure |
Semester-wise Courses and Credits |
L |
T |
P |
C |
Semester I | ||||
Communications Skills and Technical Writing |
2 |
0 |
0 |
2 |
Linear Algebra, Random Variables and Processes |
3 |
0 |
0 |
3 |
Advanced Digital Communication |
3 |
0 |
2 |
4 |
Introduction to Machine Learning |
3 |
0 |
2 |
4 |
Elective I |
3 |
0 |
2 |
4 |
Total Credits |
14 |
0 |
6 |
17 |
Semester II | ||||
Next Generation Communication Networks |
3 |
0 |
2 |
4 |
Topics in Deep Learning |
3 |
0 |
2 |
4 |
Detection and Estimation Theory |
3 |
0 |
0 |
3 |
Elective II & III |
6 |
0 |
4 |
8 |
Total Credits |
15 |
0 |
8 |
19 |
Research or Industrial Internship (Summer Semester) | 0 | 0 | 4 | 2 |
Semester III | ||||
Elective IV | 3 | 0 | 2 | 4 |
M. Tech. Thesis Preliminary Research | 0 | 0 | 12 | 6 |
Total Credits | 3 | 0 | 14 | 10 |
Semester IV | ||||
M. Tech. Thesis Research | 0 | 0 | 24 | 12 |
Total Credits | 0 | 0 | 24 | 12 |
Summary of Credit Requirements | ||||
MTech Degree Credits | 33 | 0 | 56 | 61 |
Credits for the Core Courses | 20 | 0 | 8 | 24 |
Credits for the Elective Courses | 12 | 0 | 8 | 16 |
Research Credits (including Research Seminar) | 1 | 0 | 40 | 21 |
Tentative List of Elective Subjects (the list will get updated as and when required) | |||
To be offered at | DA-IICT (Semester I and II)
Semester III electives as per the requirements |
C R Rao AIMSCS (Semester III) | |
DA-IICT |
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Admission Process
Details on the application process, admission criteria, fee structure and financial assistance can be found here