Online M.Tech. in Wireless Networks & Machine Learning (Win-ML)

Department of Electrical Engineering

Academic Programs

About the Program

The Online M.Tech. in Wireless Networks & Machine Learning (Win-ML) by IIT Kanpur empowers graduates and professionals to master next-gen communication and AI-driven systems. Combining wireless expertise with advanced Machine Learning skills, the program opens pathways to innovation, research, and career growth.

Eligibility Criteria

Institute Level Eligibility Criteria

  • Minimum CPI 5.5 or 55% marks in the qualifying degree.

Applicants may qualify via:

  • A valid score above department-stated cut-off in approved national-level exams as applicable to the program discipline (GATE/JAM/CEED/CAT/GRE/GMAT)
  • Or via IIT Kanpur's online proctored entrance test.

Department Level Eligibility Criteria

  • B.Tech./B.E./BS/BSc(4-years)/MSc in EE, ECE, CS, DS, BM, IN, Mathematics, Physics and allied disciplines.
  • Selection through written test and/or interview.

Exceptions for IITK Online Entrance Test

  • Professionals with over 5 years of relevant experience as defined by the concerned department.
  • Applicants with valid national-level test scores above the department specified cutoff.
  • Candidates nominated or sponsored by government/defense organizations.

Fee Structure

Fee Structure
Program Fee (₹) (To be Paid within 1 week of Selection) ₹1,50,000
Trimester Fee (₹) (To be paid at the begining of Registration for each Trimester) ₹25,000
Course Fees/Credits ₹4000 per credit *
Minimum Credits 144 Credits
Evalution Fee/Credits ₹400
Total Fee (₹) ₹9,33,600
Application Fee (non-refundable) ₹15,000
Continuation Fee ₹5,000 per inactive trimester.

  • 25% fee concession for candidates sponsored/nominated by the Government/PSUs/Defence Organization.
  • 15% fee concession in a year for corporate bulk nominations (5 or more candidates in a year).
  • 40% concession on Program and Course/Tuition Fees for IITK Alumni.
  • 100% concession on Program Fee and Trimester Fee for the first four trimesters for eMasters students joining M.Tech. in the same department.

* Course fees per credit may vary for interdisciplinary courses.
*** A part of Program fee (₹50,000) has to be deposited to confirm your registration in the programme.

IITK Online PG Program

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Faculty & Instructors



Alumni

Dr. Ketan Rajawat

Research Expertise:
Linear Algebra

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Alumni

Dr. Abhishek Gupta

Research Expertise:
Probability and Stochastic Processes, Analysis of Modern Wireless Networks, Simulation Techniques in Modern Wireless Networks

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Alumni

Dr. Washim Uddin Mondal

Research Expertise:
Detection and Estimation Theory

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Alumni

Dr. S. Yatindra Nath Singh

Peer-to-peer networks, Digital Switching

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Alumni

Dr. Aditya K. Jagannatham

Research Expertise:
Wireless Communications

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Alumni

Dr. Gannavarpu Rajshekhar

Research Expertise:
Coherent Imaging

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Alumni

Dr. Koteswar Rao Jerripothula

Research Expertise:
Computer Vision and Deep Learning

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Alumni

Dr. Hamim Zafar

Research Expertise:
Unsupervised Learning

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Alumni

Dr. Subrahmanya Swamy Peruru

Research Expertise:
Computer & Wireless Networks

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Alumni

Dr. Ashutosh Modi

Research Expertise:
Natural Language Processing

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Alumni

Dr. Adrish Banerjee

Research Expertise:
Information & Coding Theory

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Alumni

Dr. Rajesh M. Hegde

Research Expertise:
Speech Signal Processing, Fundamentals of Data Science

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Alumni

Dr. Rohit Budhiraja

Research Expertise:
MIMO Wireless Communications

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Alumni

Dr. Kasturi Vasudevan

Research Expertise:
Mathematical Structures of Signals and Systems

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Alumni

Dr. Tushar Sandhan

Research Expertise:
Convex Optimization

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Alumni

Dr. Sayak Ray Chowdhury

Research Expertise:
Introduction to Machine Learning

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Alumni

Dr. Rituraj

Research Expertise:
Quantum Computing and Communication

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Core

EE900E

Linear Algebra

Core

EE901E

Probability and Stochastic Processes

Elective

EE902E

Digital Communications

Elective

EE903E

Information & Coding Theory

Elective

EE928E

Introduction to Machine Learning

Elective

EE904E

Wireless Communications

Elective

EE905E

Computer & Wireless Networks

  • Prerequisite: Basic Economics and interest in technology/policy
  • Syllabus
Elective

EE906E

Image Processing

Elective

EE907E

Statistical Signal Processing

Elective

EE908E

Fundamentals of Data Science and Machine Intelligence

Elective

EE909E

Digital Switching

Elective

EE910E

Introduction to Reinforcement Learning

Elective

EE911E

Mathematical Structures of Signals and Systems

Elective

EE912E

Detection and Estimation Theory

Elective

EE913E

Computer Vision and Deep Learning

Elective

EE914E

Convex Optimization

Elective

EE915E

MIMO Wireless Communications

Elective

EE916E

Peer-to-peer networks

Elective

EE917E

5G Wireless Technologies

Elective

EE918E

Analysis of Modern Wireless Networks

Elective

EE919E

Speech Signal Processing

Elective

EE920E

Quantum Computing and Communication

Elective

EE921E

Coherent Imaging

Elective

EE922E

Natural Language Processing

Elective

EE923E

AI in Healthcare

Elective

EE924E

Unsupervised Learning

Elective

EE925E

Modern Technologies for 5G and Beyond

Elective

EE929E

AIML Projects with real-world datasets

Elective

EE926E

Machine Learning For Wireless Communications

Elective

EE927E

Simulation Techniques in Modern Wireless

Core

EE900E

Linear Algebra

Core

EE901E

Probability and Stochastic Processes

Elective

EE903E

Information & Coding Theory

Elective

EE928E

Introduction to Machine Learning

Elective

EE904E

Wireless Communications

Elective

EE905E

Computer & Wireless Networks

  • Prerequisite: Basic Economics and interest in technology/policy
  • Syllabus
Elective

EE902E

Digital Communications

Elective

EE906E

Image Processing

Elective

EE907E

Statistical Signal Processing

Elective

EE908E

Fundamentals of Data Science and Machine Intelligence

Elective

EE909E

Digital Switching

Elective

EE910E

Introduction to Reinforcement Learning

Elective

EE911E

Mathematical Structures of Signals and Systems

Elective

EE912E

Detection and Estimation Theory

Elective

EE913E

Computer Vision and Deep Learning

Elective

EE914E

Convex Optimization

Elective

EE915E

MIMO Wireless Communications

Elective

EE916E

Peer-to-peer networks

Elective

EE917E

5G Wireless Technologies

Elective

EE918E

Analysis of Modern Wireless Networks

Elective

EE919E

Speech Signal Processing

Elective

EE920E

Quantum Computing and Communication

Elective

EE921E

Coherent Imaging

Elective

EE922E

Natural Language Processing

Elective

EE923E

AI in Healthcare

Elective

EE924E

Unsupervised Learning

Elective

EE925E

Modern Technologies for 5G and Beyond

Elective

EE929E

AIML Projects with real-world datasets

Elective

EE926E

Machine Learning For Wireless Communications

Elective

EE927E

Simulation Techniques in Modern Wireless

All You Need to Know