12 Weeks Free course on AI: Knowledge Representation & Reasoning (IIT Madras)

Are you interested in learning about exploring a variety of representation formalisms and the associated algorithms for reasoning in Artificial intelligence?

IIT Madras is going to offer a free online course on AI: knowledge representation and reasoning. This course will help you understand the basics of knowledge representation and reasoning. You’ll learn how to solve problems using logic, how to build intelligent systems that can interpret natural language, reason using formal methods and more. The course is taught by Professor Deepak Khemani, who has over 20 years of experience teaching at IIT Madras. Prof. Khemani is a Professor at Department of Computer Science and Engineering. He’s also written several books and papers on the subject. This course will cover topics like knowledge representation and reasoning, search techniques, game playing and heuristic search methods. It’ll be perfect for anyone looking to learn more about this fascinating topic! Prerequisites include some exposure to formal languages, logic and programming. 

You can enroll today without paying anything – it’s completely free! If you want a certificate though, you have to register for the proctored exam that will be conducted in person at one of our designated exam centers across India. This would cost Rs. 1000/-. So what are you waiting for? Enroll now before spots run out!

Here is the course content:

  • Week 1: Introduction, Propositional Logic, Syntax and Semantics
  • Week 2: Proof Systems, Natural Deduction, Tableau Method, Resolution Method
  • Week 3: First Order Logic (FOL), Syntax and Semantics, Unification, Forward Chaining
  • Week 4: The Rete Algorithm, Rete example, Programming Rule Based Systems
  • Week 5: Representation in FOL, Categories and Properties, Reification, Event Calculus
  • Week 6: Deductive Retrieval, Backward Chaining, Logic Programming with Prolog
  • Week 7: Resolution Refutation in FOL, FOL with Equality, Complexity of Theorem Proving
  • Week 8: Description Logic (DL), Structure Matching, Classification
  • Week 9: Extensions of DL, The ALC Language, Inheritance in Taxonomies
  • Week 10: Default Reasoning, Circumscription, The Event Calculus Revisited
  • Week 11: Default Logic, Autoepistemic Logic, Epistemic Logic, Multi Agent Scenarios
  • Optional Topics A: Conceptual Dependency (CD) Theory, Understanding Natural Language
  • Optional Topics B: Semantic Nets, Frames, Scripts, Goals and Plans

Here is the introductory video on the course:

Sign up now to take this free online course on AI from IIT Madras today.

Nidhi Rai

Nidhi has been been actively blogging in different technologies such as AI / machine learning and internet technologies. Her field of interest includes AI / ML, Java, mobile technologies, UI programming such as HTML, CSS, Javascript (Angular/ReactJS etc), open-source and other related technologies.

Recent Posts

Retrieval Augmented Generation (RAG) & LLM: Examples

Last updated: 25th Jan, 2025 Have you ever wondered how to seamlessly integrate the vast…

7 days ago

How to Setup MEAN App with LangChain.js

Hey there! As I venture into building agentic MEAN apps with LangChain.js, I wanted to…

2 weeks ago

Build AI Chatbots for SAAS Using LLMs, RAG, Multi-Agent Frameworks

Software-as-a-Service (SaaS) providers have long relied on traditional chatbot solutions like AWS Lex and Google…

2 weeks ago

Creating a RAG Application Using LangGraph: Example Code

Retrieval-Augmented Generation (RAG) is an innovative generative AI method that combines retrieval-based search with large…

3 weeks ago

Building a RAG Application with LangChain: Example Code

The combination of Retrieval-Augmented Generation (RAG) and powerful language models enables the development of sophisticated…

3 weeks ago

Building an OpenAI Chatbot with LangChain

Have you ever wondered how to use OpenAI APIs to create custom chatbots? With advancements…

3 weeks ago