IITs have announced online Certificate Courses on AI & IoT

India’s premier technology institutes IIT-Gandhinagar, IIT-Kharagpur and IIT-Madras have announced online learning opportunities for students in areas of technology, IoT and artificial intelligence respectively.

About The Course

For an autonomous agent to behave in an intelligent manner it must be able to solve problems. This means it should be able to arrive at decisions that transform a given situation into a desired or goal situation. The agent should be able to imagine the consequence of their decisions to be able to identify the ones that work. In this first course on AI, we study a wide variety of search methods that agents can employ for problem-solving.

  • In a follow-up course – AI: Knowledge Representation and Reasoning – we will go into the details of how an agent can represent its world and reason with what it knows. These two courses should lay a strong foundation for artificial intelligence, which the student can build upon.
  • A third short course – AI: Constraint Satisfaction Problems – presents a slightly different formalism for problem-solving, one in which the search and reasoning processes mentioned above can operate together.

INTENDED AUDIENCE

This is the first course on Artificial Intelligence. While the intended audience is both UG and PG students studying Computer Science, in fact, anyone comfortable with talking about algorithms should be able to do the course.

INDUSTRY SUPPORT

Any industry that is involved in the development of AI applications. This not only includes software companies (like Microsoft, Google, and Facebook) but also manufacturing companies like Ford and General Electric, and retail companies like Amazon and Flipkart.

Course Layout

  • Week 0: Introduction: History, Can Machine think? Turing Test, Winograd Schema Challenge, Language and Thought, Wheels & Gears
  • Week 1: Introduction: Philosophy, Mind, Reasoning, Computation, Dartmouth Conference, The Chess Saga, Epiphenomena
  • Week 2: State-Space Search: Depth First Search, Breadth-First Search, Depth First Iterative Deepening
  • Week 3: Heuristic Search: Best First Search, Hill Climbing, Solution Space, TSP, Escaping Local Optima, Stochastic Local Search
  • Week 4: Population-Based Methods: Genetic Algorithms, SAT, TSP, emergent Systems, Ant Colony Optimization
  • Week 5: Finding Optimal Paths: Branch & Bound, A*, Admissibility of A*, Informed Heuristic Functions
  • Week 6: Space Saving Versions of A*: Weighted A*, IDA*, RBFS, Monotone Condition, Sequence Alignment, DCFS, SMGS, Beam Stack Search
  • Week 7: Game Playing: Game Theory, Board Games and Game Trees, Algorithm Minimax, AlphaBeta, and SSS*
  • Week 8: Automated Planning: Domain-Independent Planning, Blocks World, Forward &Backward Search, Goal Stack Planning, Plan Space Planning
  • Week 9: Problem Decomposition: Means Ends Analysis, Algorithm Graphplan, Algorithm AO*
  • Week 10: Rule-Based Expert Systems: Production Systems, Inference Engine, Match-Resolve-Execute, Rete Net
  • Week 11: Deduction as Search: Logic, Soundness, Completeness, First Order Logic, Forward Chaining, Backward Chaining
  • Week 12: Constraint Processing: CSPs, Consistency Based Diagnosis, Algorithm Backtracking, Arc Consistency, Algorithm Forward Checking

Reference Books

1. Stefan Edelkamp and Stefan Schroedl. Heuristic Search: Theory and Applications, Morgan Kaufmann, 2011.
2. John Haugeland, Artificial Intelligence: The Very Idea, A Bradford Book, The MIT Press, 1985.
3. Pamela McCorduck, Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence, A K Peters/CRC Press; 2 edition, 2004.
4. Zbigniew Michalewicz and David B. Fogel. How to Solve It: Modern Heuristics. Springer; 2nd edition, 2004.
5. Judea Pearl. Heuristics: Intelligent Search Strategies for Computer Problem Solving, Addison-Wesley, 1984.
6. Elaine Rich and Kevin Knight: Artificial Intelligence, Tata McGraw Hill, 1991.
7. Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach, 3rd Edition, Prentice-Hall, 2009.
8. Eugene Charniak, Drew McDermott: Introduction to Artificial Intelligence, Addison-Wesley, 1985.
9. Patrick Henry Winston: Artificial Intelligence, Addison-Wesley, 1992.

Course certificate

  • The course is free to enroll in and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centers.
  • The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
    Date and Time of Exams: 29 October 2022 Morning session 9 am to 12 noon; Afternoon Session 2 pm to 5 pm.
  • Registration URL: https://nptel.ac.in/courses/106106226
  • The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, they will be mentioned then.

CRITERIA TO GET A CERTIFICATE

  1. Average assignment score = 25% of the average of the best 8 assignments out of the total 12 assignments given in the course.
  2. Exam score = 75% of the proctored certification exam score out of 100
  3. Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF THE AVERAGE ASSIGNMENT SCORE >=10/25 AND THE EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

  • The certificate will have your name, photograph, and score in the final exam with the breakup. It will have the logos of NPTEL and IIT Madras. It will be e-verifiable at nptel.ac.in/noc.
  • Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

Disclaimer: This information is covered based on the latest research and development available. However, it may not fully reflect all current aspects of the subject matter.

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