M.Tech. (ICT)

Program Overview Master of Technology in Information and Communication Technology – M.Tech. (ICT) is a full-time two-year (four semesters) program. The program has been specially designed to meet the increasing needs of professionals who would be able to respond to the convergence between computers and communication systems. The program aims to provide exposure to students who wish to build a professional career in ICT, working at the intersection of technology, research, and development in the areas of Machine Learning and applications to speech, image and vision, natural language processing and others, Data Analytics, Cyber Security, Distributed Computing, Software Engineering, Signal Processing, Embedded Systems, VLSI Subsystem Design, FPGA, Low-power VLSI Design and Nano electronics.

The Program curriculum includes four specializations tracks that provide a strong foundation and advanced courses in each track. This program tries to leverage the strength and diversity of our faculty and currently offers the following specialization tracks:

  • Machine Learning
  • Signal Processing and Machine Learning
  • Software Systems
  • VLSI and Embedded Systems

Apart from courses, students are required to pursue one full year (two 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. (ICT) specializing in the respective track. 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 ICT domain using modern technologies and tools, and will have the ability to demonstrate excellent analytical and logical problem-solving skills. Apart from receiving rigorous exposure to various areas of scholastic study and research, students are at the same time groomed to cultivate sound professional ethics.

The structure of the curriculum is broadly classified into 4 categories. The first category, referred to as Program Core, is a set of compulsory courses mandatory for every student in the program. Specialization Core courses impart domain knowledge, foundational as well as advanced, in respective specializations, and are offered to students of respective specializations. The third category is Electives, which may or may not be chosen to align with a specific specialization, and allows one to go beyond his/her own specialization. The fourth one is the Research Thesis, spread over the third and fourth semesters. A student is required to carry out research under the supervision of a faculty member at DA-IICT in an area of mutual interest.

Program Educational Objectives

  • Provide students with a strong foundation of core principles in specialized areas of ICT.
  • Provide students adequate knowledge and hands-on experience in a specialization selected by the students
  • Prepare students to solve and analyze real-world problems using modern tools and research inputs
  • Prepare students for research and development in industry and organization and motivate them for higher studies. Prepare students for their contributions in research and development by pursuing higher studies in the field of engineering, science, business, or administration
  • Prepare students with the necessary theoretical background and technical skills to work professionally as software engineer, system analyst, research scientist, entrepreneur, software developer, and teaching professionals

Program Outcomes

After successful completion of the MTech program students will have:

  • Essential technical and practical knowledge for solving real-world problems in the field of ICT domain.
  • Ability to demonstrate excellent programming, analytical, logical and problem solving skills that would bridge digital divide between urban and rural developments.
  • Ability to use modern engineering tools and technologies necessary for engineering practice in industry and R&D organizations.
  • Ability to acquire social and ethical attributes that enable them in applying their skills for societal needs.
  • Ability to communicate effectively both orally and written.
Semester-wise Program Structure
Semester Courses Credit Structure
Semester 1 Program Core 1 1-0-4-3
Program Core 2 2-0-0-2
Specialization Core 1 3-0-0-3
Specialization Core 2 3-0-2-4
Specialization Core 3 3-0-2-4
Semester 2 Specialization Core 4 3-0-0-3
Specialization Core 5 3-0-2-4
Specialization Core 6 3-0-2-4
Elective 3-0-0/2-3/4
Semester 3 Specialization Core 7 3-0-0-3
Specialization Core 8 3-0-2-4
Thesis 0-0-12-6
Semester 4 Thesis(Continuation) 0-0-26-13
Total Credits   30-0-52/54- 56/57

The credit structure of a course is given by a sequence of 4 numbers: (1) Number of lecture hours per week (L), (2) Number of tutorial hours per week (T), (3) Number of lab hours per week (P), and (4) the Total credit of the course (C). 1 lecture hour/week contributes 1 credit; 1 tutorial hour/week contributes 1 credit; 2 laboratory hours/week contribute 1 credit

The curriculum mandates a minimum of 56 credits, 37 earned through coursework and 19 through research credits. Out of the 37 required coursework credits, 5 credits are allocated to compulsory courses (Program core), 29 credits are allocated to Specialization core courses, 3 credits are allocated to an elective.

The distribution of courses for M.Tech. (ICT) degree is as under:

Subject area No. of credits
Program Core courses 5
Specialization Core courses 29
Elective courses 3
Thesis work 19
Total credits 56

Course Details

The following is a representative list of courses. There may be a few minor changes and updates to this list.

Semester I
  Machine Learning Signal Processing and Machine Leaning Software Systems VLSI and Embedded Systems
Program Core Programming Lab
Communication Skills and Technical Writing
Specialization Core Probability and Random Variables Linear Algebra, Random Variables and Random Processes Probability and Random Variables Introduction to Embedded Systems
Linear Algebra and Optimization Advanced Digital Signal Processing Advanced Algorithms Basics of VLSI
Accelerated Computing Introduction to Machine Learning Advanced Software Engineering Digital Design using HDL and FPGA
Semester II
  Machine Learning Signal Processing and Machine Leaning Software Systems VLSI and Embedded Systems
Specialization Core
(Any Three)
Advanced Image Processing Detection and Estimation Information Security Digital System Architecture
Pattern Recognition and Machine Learning Adaptive Signal Processing Distributed Systems Embedded System Design
Information Retrieval Topics in Deep Learning Distributed Databases VLSI Subsystem Design
Brain Cognitive Science Wavelet Signal Processing Advanced Computer Networks Analog IC Design
Computational Shape Modeling      
Semester III
  Machine Learning Signal Processing and Machine Leaning Software Systems VLSI and Embedded Systems
Specialization Core (Any two) Computer Vision Adversarial Machine Learning Software Testing and Verification Low Power VLSI Design
Deep Learning Accelerated Computing Blockchains and Cryptocurrencies. Selected Topics in VLSI
  Computer Vision    
Thesis M.Tech Thesis
Semester IV
  Machine Learning Signal Processing and Machine Leaning Software Systems VLSI and Embedded Systems
Thesis M.Tech Thesis (Continuation)

Admission Process

Details on the application process, admission criteria, fee structure and financial assistance can be found here

Back to Top
Back to Top