Educational Programs

50-week Foundations of Modern Machine Learning

The course is designed exclusively for the benefit of second year undergraduate engineering students (in third or fourth semesters). Course starts from August 2022.


Applications of machine learning have grown beyond expections and have started showing up in various domains. In many of the successful cases, the applications have been guiding professionals to make well-informed decisions. Technology innovation hub of IIIT Hyderabad (iHub-Data) having strong research programs in machine learning, image processing, computer vision, robotics, natural language processing, pattern recognition and speech processing, is pleased to announce a 50-week foundation program in machine learning for undergraduate engineering students who are in their second year of study (either in third semester or fourth semester) across India, slated to commence from August 2022 onwards.

Who can participate?

  • Students pursuing 4-year UG program in engineering/technology
  • Students should be in their third/fourth semesters (second year of engineering).
  • Students should be studying in an AICTE recognised institution or a technical institution of repute in India.
  • Students should be able to spare at least three hours every week for learning the course.

What makes this program unique?

  • 50-week certificate program in Foundations of Modern Machine Learning
  • Equivalent to a typical 4 credit course as per UGC/AICTE norms
  • Live online lectures and hands-on sessions with personalised learning experience
  • Includes over 40 independent projects, quizzes and assignments.
  • Equal focus on foundation and practices
  • Discussions with eminent professionals

What is the qualifying criteria?

  • Strong interest to learn fundamentals of Machine Learning and Deep Learning
  • Keen programming interest in Python in Colab environment
  • Want to learn applications of Linear Algebra, Probability and Statistics

Frequently Asked Questions (FAQs)

How is this course different from other courses?
This program uniquely combines the benefits of an in-class program with the flexibility of online learning. Recorded classes give the participants the flexibility of learning at their pace. Live interactions with the faculty and mentors help them to clarify their doubts and queries.

Will I receive a certificate at the end of the course?
Yes, a certificate of achievement from IIIT-H will be awarded upon successful completion of the course.

How will my doubts/queries be resolved in the online class?
Live sessions with the IIIT-H faculty will enable the participants to clear their doubts. Additionally, mentors will be available to clear doubts during the one to one mentoring sessions. Mentors and Project Associates are there to help the participant with better solutions and workarounds.

Who will be teaching the course?
Recorded and live sessions will be provided by the IIIT-H faculty in conjunction with mentors with considerable AI/ML expertise. Industry experts will also contribute to the learning outcomes through occasional sessions. Members of faculty would include Prof CV Jawahar, Prof Anoop M Namboodiri, Dr Ravi Kiran S among others.

What is the expected weekly time commitment?
Participants are expected to commit 3 hours a week to fully benefit from the program. This will include the online sessions and time devoted for learning and assignments as well.

How will I be evaluated during the course?
A holistic approach would be followed where participants would be evaluated continuously. Quizzes, assignments, discussions and attendance would be used for evaluation of performance.

How will I get access to online labs?
All participants would get access to the online labs right from the start of the program.

Does the course have a deferral policy?

When will the live classes be conducted?
The live interactive sessions will usually be conducted on weekends or outside working hours of day.

What if I miss a live class?
It is advisable not to miss the live sessions with the faculty. However, in the event of missing a class,  recording of the session would be made available for a limited period.

What are the system/internet requirements needed to attend the course?
A laptop/desktop and a stable internet connection is essential to attend the course.

Will I be able to access the learning contents even after completing the course?
The laboratory contents would be built independently by all participants, as part of attending the course. Recorded sessions of classes are set to expire automatically after a fixed duration.

Does IIIT Hyderabad offer a course on Modern Machine Language on-campus ?
No, there is no equivalent on-campus program. IIIT Hyderabad has curated this course, exclusively as an online program.

What is the language of instruction for these courses? Are they available in other regional languages?
All our program courses are taught in English. Hence, a minimum proficiency in English language is expected to participate in the program.

Are there any communication groups on WhatsApp, Telegram etc for the online program on Modern Machine Learning?
Individual email addresses from IIIT domain would be extended to all participants. Discord would be another source of communicating.

What should be done if there is an error with registration?
Please send us your registered email-id,  application number and a screenshot of the error/issue with relevant description to

Is there an attendance policy for this program?
Yes. Participants are expected to have minimum 75% attendance.

Can we have any hands-on training part (practical lab sessions) ?
All laboratory sessions would be on cloud-based platforms, which would be carried out in week days at a convenient time of participants.

Who will be issuing the certificate ?
IIIT Hyderabad will be issuing the certificate of completion of the course.

Are there any projects to work after the course ?
Those who complete the course with a good rating might be considered for (a) summer internships (with stipend) (b) lateral entry admission or (c) working on research projects at IIIT Hyderabad.

Any internship/placement support ?
Participants who perform reasonably well would be extended opportunity to participate in long-term internship programs (with stipend) organised at IIIT Hyderabad

I am a working-professional. Can I join this course ?

This course is exclusively meant for undergraduate engineering students. For working professionals, the appropriate course is

I am a teacher in a technical institute. Can I join this course ?

This course is exclusively meant for undergraduate engineering students. For members of faculty, the appropriate course is

What is the general opinion about this Course ?

A few UG students who completed the course were contacted for their opinions about the course. Please hear them speaking their mind out.

Important Dates to remember

  • Last date of registering for aptitude exam (Rs 500) : 15 June 2022
  • Online aptitude examination : 26 June 2022 (8pm to 9pm) link would be sent via email.
  • Payment of Registration Fee : Closed
  • Preparatory Sessions (from) : 22 July 2022
  • Regular FMML Sessions from : 13 Aug 2022

How to Register

  • The last date for registration was over on 15 June 2022.
  • Names of those who have been admitted are published here. This includes list of provisional admissions too.
  • The aptitude examination would test for reasonable proficiency in english language (+2 level), basic maths (+2 level), and reasoning skills, all of which are deemed essential for this course.


  • Introduction to ML
  • Machine Learning Components: Data, Model, Evaluation
  • Revisiting Nearest Neighbor Classification
  • Retrieval, Performance Evaluation and Metrics
  • Decision Trees
  • Linear Classifier
  • SVM
  • Representing Textual Data,  Aadhar: Sequences matching
  • Perceptrons and gradient descent
  • Loss functions and gradient descent
  • Regression
  • Clustering
  • Feature selection and PCA
  • Multi Layer Perceptron
  • Probabilistic ML models
  • Deep Learning Architectures

Grading Policy

  1. 25% weightage for assignments (github)
  2. 75% weightage for examinations (online)
  3. Grades
    Less than 40% – No certificate
    40 – 59% – Completion Certificate
    60 – 74% – B Grade
    75 – 89% – A Grade
    90% above – O Grade (Outstanding)

For any clarification,


Ph: +91 40 6653 1789 (Mon-Fri 0930h to 1730h)

Grade Certificate

Certificates issued to participants of FMML-2022.

Program Coordinators:

Teaching Assisstants: