Student Training Program on AI/ML – Aug 2023
– Weekend Classes at IIIT Hyderabad
This 50-week student-training program on artificial intelligence/machine learning is intended for undergraduate engineering students pursuing 4-year B Tech programs approved by AICTE, in technical institutions in and around Hyderabad.
Admission would be restricted to two students per institution, recommended by HoD/Head of Institution. Students, who are within commuting distance from IIIT Hyderabad would only be considered to undergo the program.
The course comprises of a fine mix of theory sessions with accompanying practical tutorial sessions on topics related to AI/ML
Classes would be conducted during weekends – on all Sundays, from 08:30 am to 11:30 am – covering theory sessions as well as tutorials.
The course fee for this program is NIL, but participants would need to furnish Rs 10,000 as caution deposit, which would be returned upon successful completion of the program.
This project is supported under the scheme of National Mission of Interdisciplinary Cyber Physical Systems, Dept of Science and Technology, Govt of India.
Frequently Asked Questions (FAQs)
Will I receive a certificate at the end of the course?
Yes, a certificate of competency with grades would be awarded upon successful completion of the course.
Who will be teaching the course?
The course would be provided by the IIIT-H faculty with considerable AI/ML expertise.
What is the expected time commitment?
For maximum program benefits, participants are required to dedicate three hours every weekend.
How will I be evaluated during the course?
A holistic approach would be followed where participants would be evaluated continuously. Attendance is one of the important factor that would be used for evaluation of performance.
When will the classes be conducted?
The sessions would be conducted on every weekends (Sundays).
What if I miss a class?
It is advisable not to miss the sessions with the faculty.
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 essential.
Are there any communication groups on WhatsApp, Telegram etc for the offline program on Modern Machine Learning?
Individual email addresses from IIIT domain would be extended to all participants.
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 firstname.lastname@example.org
Is there an attendance policy for this program?
Yes. Participants are expected to have minimum 75% attendance.
Who will be issuing the certificate ?
iHub-Data, IIIT Hyderabad will be issuing the certificate of competency after 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) admission for MS program 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/without 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 https://iiit-h.talentsprint.com/aiml/index.html
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 https://csedu.iiitd.ac.in/program.html There could also be similarly named courses at Coursera or SWAYAM/NPTEL offered in fully online mode.
Also, Hub conducts an FMML course that requires Rs. 10,000 as fee and this AI/ML course for a caution deposit. Are these the same programs?
The FMML program differs from the AI/ML weekend sessions in terms of payment and mentorship. FMML is a paid program, and the fees mainly cover the cost of TA-ship, where mentors guide students in small groups. However, for the AI/ML weekend sessions, mentorship is not deemed necessary at this stage since all participants are expected to be high-performing students.
Announcement in Press: https://www.iiit.ac.in/news/StudentTrainingProgramonAI/ML/
Process Steps for Joining Weekend Training Program:
- Heads of institutes will register with their credentials.
- iHub-Data will verify and seek details of student toppers from heads of institutes.
- Only two toppers from regular students, are eligible. (First years/Graduates aren’t eligible)
- Coordinator from iHub-Data will reach out to students with payment link.
- Once payment is confirmed, names of students will appear below.
- Students attempting to join this program by any other means would be disqualified.
- Admission will be limited to first 100 nominations.
- Last date for receiving registrations from institutes is 20 July 2023
However, for those who are unable to secure admission, we invite you to join our online program titled “Foundations of Modern Machine Learning – August 2023” which can be accessed through the following link: (Click here)
Admissions for the batch 2023-2024 have been closed.
Regular Sessions from : 20 Aug 2023
Venue : H-205 (Himalaya Block), IIIT Hyderabad
- Introduction to ML
- Machine Learning Components: Data, Model, Evaluation
- Revisiting Nearest Neighbor Classification
- Retrieval, Performance Evaluation and Metrics
- Decision Trees
- Linear Classifier
- Representing Textual Data, Aadhar: Sequences matching
- Perceptrons and gradient descent
- Loss functions and gradient descent
- Feature selection and PCA
- Multi Layer Perceptron
- Probabilistic ML models
- Deep Learning Architectures
- 25% weightage for assignments (GitHub)
- 75% weightage for examinations (Online)
Less than 40% – No certificate
40 – 59% – Completion Certificate
60 – 74% – B Grade
75 – 89% – A Grade
90% above – Outstanding
The assignment will be evaluated on a 5-point scale, with a minimum of 1 point will be awarded for submission.
The total points allotted may be adjusted based on the number of questions addressed, with each answered question contributing to the final score.
To earn points, each answered question should be supported by a clear and well-reasoned explanation.
Module-Wise Examination Date and Time:
|Module Number||Module Name||Examination Date||Time|
|1||Representation and Learning||07.10.2023||8.30 pm to 9.30 pm|
|2||Appreciating, Interpreting and Visualizing Data||04.11.2023||8.30 pm to 9.30 pm|
|3||Classification 1: Nearest neighbour method||25.11.2023||8.30 pm to 9.30 pm|
|4||Perceptron and Gradient Descent||23.12.2023||8.30 pm to 9.30 pm|
|5||Classification 2: Powerful popular classifiers||20.01.2024||8.30 pm to 9.30 pm|
|6||Regression and Regularization||10.02.2024||8.30 pm to 9.30 pm|
|7||Unsupervised Learning||09.03.2024||8.30 pm to 9.30 pm|
|8||Probabilistic Perspective||06.04.2024||8.30 pm to 9.30 pm|
|9||MLP and CNN||04.05.2024||8.30 pm to 9.30 pm|