IIT Madras introduces free online programme on artificial intelligence: Report

IIT Madras will offer the eight-week online programme on NPTEL platform from January 24 to March 8, 2022.

IIT Madras introduces free online programme on artificial intelligence: Report IIT Madras (Source: Official)
Vagisha Kaushik | Nov 8, 2021 - 5:35 p.m. IST
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NEW DELHI: The Indian Institute of Technology, Madras has introduced a free online programme on artificial intelligence which will be offered from January 24 to March 8, 2022, as per a Telegraph India report.

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While the duration of the online course, Artificial Intelligence: Constraint Satisfaction Problems is eight weeks, the course will be offered on the National Program on Technology Enhanced Learning (NPTEL) platform, the report said.

Both undergraduate and postgraduate students pursuing computer science or any degree, can apply for the online programme. Professionals and other interested participants with prerequisite knowledge in basics of Computer Science, can also learn.

While the online programme is free, the students wishing for a certificate will have to register and appear for an examination conducted by the institute at any one of the exam centres, the report said.

The exam will be optional and charge a fee of Rs 1,000 and the students will get an e-certificate. Students will receive a certificate only if they get an average assignment score of 10 out of 25, and an average exam score of 30 out of 75.

Exams will be conducted on March 27, 2022. Morning session will be held from 9am to 12 noon and afternoon session from 2pm to 5pm.

Deepak Khemani, professor at Department of Computer Science and Engineering at IIT Madras will conduct the programme.

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Programme Layout:

  • Constraint satisfaction problems (CSP), examples.
  • Constraint networks, equivalent and projection networks.
  • Constraint propagation, arc consistency, path consistency, i-consistency.
  • Directional consistency and graph ordering, backtrack free search, adaptive consistency.
  • Search methods for solving CSPs, lookahead methods, dynamic variable and value ordering.
  • Lookback methods, Gaschnig’s back jumping, graph based backjumping, conflict directed backjumping, and combing lookahead with look back, learning.
  • Model based systems, model based diagnosis, truth maintenance systems, planning as CSP. Wrapping up.

Students can find other details about the course here.


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