Electronics and Communication Engineering

The Master of Technology (Online) programme in Electronics and Communication Engineering is offered by the Division of Electrical, Electronics, and Computer Sciences. The programme is designed for early-career professionals (with 2-10 years of experience) to strengthen their fundamentals and expose them to cutting-edge topics in the fast-changing areas of communications, networks, signal processing and information sciences, and high-frequency c ircuits and systems. The coursework contains core courses, which provide the necessary foundation, and several elective courses, which provide exposure to the state-of-the-art and advanced material. These learnings are coupled with a semester-long capstone project that enables the student to apply the knowledge gained to a project relevant to the industry. The courses are taught online by faculty from the Department of ECE.


Program Structure [August 2023 batch onwards]

 

    • Core courses (16 credits): These are typically taken in the first and second semesters.

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

       

    • Sample Elective courses (at least 20 credits):
      • Semiconductor devices for nanoelectronics
      • Antenna Theory and Practice
      • Radio Frequency Integrated Circuits and Systems
      • Advanced Deep Representation learning
      • Communication Systems Design
      • Students may also take courses from any of the three streams as an elective.These are the minimum number of elective credits. More may be taken as well.
  • Project (28 credits): This involves a two-term project, with 10 credits in the first term followed by a mid-term evaluation, and 18 credits in the second term with a final evaluation. The second term project is taken up only after all courses are completed in prior semesters.

    Student will propose the topic in consultation with their Guide from within the organization, and an IISc faculty mentor will approve project goals. The faculty mentor will offer high-level feedback on the project and its progress, and coordinate the evaluations, while the in-house company Guide will offer active feedback and close support. The evaluation committee, which includes the faculty mentor and company guide, is appointed by the PCC.

 


Program Structure [August 2022 batch]

    • Core courses (15 credits): These are typically taken in the first and second semesters.

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

       

    • Elective courses (at least 21 credits): See sample courses above
  • Project (28 credits): See instructions for project above


Program Structure [For 2021 batch]

 

    • Core courses (12 credits): These are typically taken in the first and second semesters. The courses will have a new course code since the credits re different from the regular M.Tech. on account of some revision in syllabus and homework/assignments/online labs.

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

       

    • Elective courses (at least 24 credits): See sample courses above
  • Project (28 credits): See instructions for project above