★ Approved by the CCE Committee, IISc Bengaluru ★ Est. 1975

Centre for Continuing Education · IISc Bangalore

Electronics & Communication Engineering

Organisations that have entered into a Memorandum of Agreement with IISc, enabling their employees to enrol in the M.Tech. (Online) programme.

M.Tech (Online) · Stream

Electronics & Communication Engineering

Offered by the Division of Electrical, Electronics and Computer Sciences (EECS), this programme is designed for early-career professionals with 2–10 years of experience.

The programme strengthens fundamentals and exposes students to cutting-edge topics in communications, networks, signal processing, information sciences, and high-frequency circuits and systems. All courses are taught online by faculty from the Department of ECE.

Programme at a Glance

Total Credits64
Core Credits8
Soft Core Credits12 (choose 3)
Elective Credits16
Project Credits28
CommencedAugust 2021

Total Programme Credits

Core Course Credits

Soft Core Credits (choose 3 of 8)

Project Credits

Mandatory Foundation

Core Courses — 8 Credits

Two mandatory core courses providing the mathematical and probabilistic foundations required for all subsequent ECE stream courses and the project. Typically completed in the first semester.

Random Processes

3:1 Credits

Probability theory, stochastic processes, Markov chains, power spectral density, and their fundamental applications in communications and signal processing systems.

Linear Algebra

3:1 Credits

Matrices, vector spaces, eigenvalues, SVD, and linear transformations — the mathematical backbone of modern signal processing, communications, and machine learning for ECE.

Directed Specialisation

Soft Core Courses — 12 Credits (Choose 3 of 8)

Students select 3 courses (12 credits) from 8 offered soft core options, allowing directed specialisation within ECE. These expand on communication systems, signal processing, circuit design, and machine learning applications for wireless systems.

Digital Communications

Modulation schemes, channel coding, digital receiver design, and performance analysis for modern communication systems.

Statistical Inference

Statistical inference methods for engineers and data scientists, covering parameter estimation and hypothesis testing.

Communication System Design

End-to-end design of communication systems from requirements through RF front-end to baseband processing.

Digital Image Processing

Image acquisition, filtering, transforms, compression, and feature extraction for vision systems and multimedia applications.

Process Technology & System Engineering

Semiconductor process technology, device physics, and system-level engineering for chip and product design.

Antennas & Circuits for Communications/Radar

Antenna design, RF circuit fundamentals, and system-level design for emerging communication and radar applications.

Wireless Communications

Propagation models, cellular systems, MIMO, OFDM, and 5G/6G technologies for modern wireless networks.

Machine Learning for Wireless Communications

Applying deep learning, neural networks, and AI-driven methods to channel estimation, beam management, and network optimisation.

Open Electives

Remaining Elective Credits — 16 Credits

The remaining 16 course credits are taken freely from any of the 30+ electives offered across all three M.Tech. (Online) streams, enabling interdisciplinary depth across AI, data science, and advanced ECE topics. Sample electives from prior batches include:

Radio Frequency Integrated Circuits & Systems

RFIC design fundamentals, LNA, mixers, VCOs, and system-level considerations for wireless transceivers.

Detection & Estimation Theory

Optimal detection, parameter estimation, Kalman filtering, and their applications in radar, sonar, and communication receivers.

Cross-Stream AI & Data Science Electives

Students may take electives from the AI and DSBA streams — including Deep Learning, Data Analytics, Reinforcement Learning, and more — to broaden interdisciplinary skills.

Capstone Work

Project — 28 Credits across 3 Phases

Students begin the project only after successfully completing all core and soft core course credits. Each phase maps to one semester. The final phase can only be completed in a regular semester — not a summer term.

Phase 1 — Topic Identification

2 Credits

Identify project topic with the company guide. Submit a written report outlining the problem statement, proposed approach, and initial feasibility assessment.

Phase 2 — Development & Mid-term

12 Credits

Core project development. Ends with a mid-term evaluation by a committee of the IISc faculty mentor, company guide, and PCC-nominated faculty. Submit written progress report.

Phase 3 — Final Evaluation

14 Credits

Thesis completion and final evaluation. Must be in a regular semester only (not summer). All course credits must be completed before Phase 3 begins.

IISc Faculty Mentor

Approves project goals, provides high-level academic direction, and coordinates mid-term and final evaluations. Project topic must be broadly related to ECE and subject to PCC approval.

Company Guide

Provides active in-house guidance and close support. Member of the evaluation committee appointed by the PCC. Must hold a PhD or 5+ years post-Masters experience.

Programme Focus Areas

Four Pillars of the ECE Stream

The ECE programme curriculum is structured around four major knowledge pillars, each representing a critical domain in modern electronics and communication engineering.

Communications & Networks

Wireless, 5G/6G, digital modulation, MIMO systems, network protocols, and communication system design.

Signal Processing & Information Sciences

Detection, estimation, image processing, statistical inference, and information-theoretic foundations.

High-Frequency Circuits & Systems

RF/microwave circuits, RFIC design, antennas, radar systems, and process technology for emerging applications.

AI & Machine Learning for ECE

Applying deep learning, neural networks, and AI to wireless communications, radar signal processing, and intelligent systems.

Programme History

Structure by Batch

The programme structure has evolved significantly since 2021. Select your batch to see the applicable core, elective, and project credit requirements.

August 2026 Batch Onwards — Current Structure

Core Courses — 8 Credits

  • Random Processes (3:1)
  • Linear Algebra (3:1)

Soft Core Courses — 12 Credits (choose 3 from 8)

  • Digital Communications (3:1)
  • Statistical Inference for Engineers and Data Scientists (3:1)
  • Communication System Design (3:1)
  • Digital Image Processing (3:1)
  • Process Technology and System Engineering (3:1)
  • Antennas and Circuits for Emerging Communication and Radar (3:1)
  • Wireless Communications (3:1)
  • Machine Learning for Wireless Communications (3:1)

Remaining Electives — 16 Credits

From any of the 30+ electives offered across all three M.Tech. (Online) streams.

Project — 28 Credits

Phase 1: 2 credits (topic + written report) · Phase 2: 12 credits (mid-term eval) · Phase 3: 14 credits (final eval, regular semester only).

August 2023, 2024 & 2025 Batches

Core Courses — 16 Credits (first two semesters)

  • Random Processes (4 credits)
  • Digital Communications (4 credits)
  • Statistical Inference for Engineers and Data Scientists (4 credits)
  • Linear Algebra (4 credits)

Sample Elective Courses — Minimum 20 Credits

  • Process Technology and System Engineering (4 credits)
  • Antennas and Circuits for Emerging Communication and Radar (4 credits)
  • Radio Frequency Integrated Circuits and Systems (4 credits)
  • Machine Learning for Wireless Communication (4 credits)
  • Communication Systems Design (4 credits)
  • + Any elective from the 30 offered across all three streams

Project — 28 Credits (in-house with company guide and IISc mentor)

August 2022 Batch

Core Courses — 15 Credits

  • Random Processes (3:1)
  • Digital Communications (3:1)
  • Statistical Inference for Engineers and Data Scientists (3:1)
  • Linear Algebra (3:0)

Elective Courses — Minimum 21 Credits

From available offerings. See current sample electives above.

Project — 28 Credits

2021 Batch

Core Courses — 12 Credits

  • Random Processes (3:1)
  • Digital Communications (3:1)
  • Detection and Estimation (3:1)

Note: Courses had new course codes as credits differed from regular M.Tech. on account of revisions in syllabus, homework, assignments, and online labs.

Elective Courses — Minimum 24 Credits

From available offerings.

Project — 28 Credits

Apply Now

Interested in the ECE Stream?

Admissions for the 2026 batch (August 2026 structure) are now open. Ask your organisation to nominate you — or check if your company already has an MoA with IISc.