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Last updated:

September 25, 2023

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FREE

This course includes:

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Description

Artificial Intelligence. Instructors: Prof. Anupam Basu and Prof. Sudeshna Sarkar, Department of Computer Science and Engineering, IIT Kharagpur.

The course will cover basic ideas and techniques underlying the design of intelligent computer systems. Topics include: Introduction to AI and intelligent agents; Solving problems by searching, heuristic search techniques, constraint satisfaction problems, stochastic search methods; Knowledge and reasoning: propositional logic, first order logic, situation calculus; Theorem proving in first order logic; Planning, partial order planning; Uncertain knowledge and reasoning; Learning: overview of different forms of learning, learning decision trees, neural networks; Introduction to natural language processing. (from nptel.ac.in)

Course Curriculum

  • Lecture 01 – Introduction to Artificial Intelligence Unlimited
  • Lecture 02 – Intelligent Agents Unlimited
  • Lecture 03 – State Space Search Unlimited
  • Lecture 04 – Uninformed Search: Depth First Search, Breadth First Search Unlimited
  • Lecture 05 – Informed Search: Heuristics – A*, Greedy Search, Uniform-Cost Search Unlimited
  • Lecture 06 – Informed Search: A* Search, Iterative-Deepening A* Unlimited
  • Lecture 07 – Two Player Games: Game Tree Search Unlimited
  • Lecture 08 – Two Player Games: Game Tree Search (cont.) Unlimited
  • Lecture 09 – Constraint Satisfaction Problems Unlimited
  • Lecture 10 – Constraint Satisfaction Problems (cont.) Unlimited
  • Lecture 11 – Knowledge Representation and Logic: Propositional Logic Unlimited
  • Lecture 12 – Interface in Propositional Logic Unlimited
  • Lecture 13 – First Order Logic Unlimited
  • Lecture 14 – Reasoning using First Order Logic Unlimited
  • Lecture 15 – Resolution in First Order Predicate Logic Unlimited
  • Lecture 16 – Rule Based Systems Unlimited
  • Lecture 17 – Rule Based Systems (cont.) Unlimited
  • Lecture 18 – Semantic Net Unlimited
  • Lecture 19 – Reasoning in Semantic Net Unlimited
  • Lecture 20 – Frames Unlimited
  • Lecture 21 – Introduction to Planning Problems Unlimited
  • Lecture 22 – Planning: Forward Search, Backward Search, Strips Planning Unlimited
  • Lecture 23 – Planning: Partial Order Planning (cont.) Unlimited
  • Lecture 24 – Planning Graph and Graphplan Algorithm Unlimited
  • Lecture 25 – Rule Based Expert System Unlimited
  • Lecture 26 – Reasoning with Uncertainty: Certainty Factors Unlimited
  • Lecture 27 – Reasoning with Uncertainty: Certainty Factors (cont.) Unlimited
  • Lecture 28 – Reasoning with Uncertainty: Basics of Probability Theory Unlimited
  • Lecture 29 – Reasoning with Uncertainty: Bayes’ Rule, Belief Network Unlimited
  • Lecture 30 – Fuzzy Reasoning: Fuzzy Logic, Fuzzy Sets Unlimited
  • Lecture 31 – Fuzzy Reasoning: Fuzzy Sets (cont.) Unlimited
  • Lecture 32 – Introduction to Learning – Definition of Machine Learning, Concept Learning Unlimited
  • Lecture 33 – Introduction to Learning – The Problem of Concept Learning Unlimited
  • Lecture 34 – Rule Induction and Decision Trees I Unlimited
  • Lecture 35 – Rule Induction and Decision Trees II Unlimited
  • Lecture 36 – Learning using Neural Networks I Unlimited
  • Lecture 37 – Learning using Neural Networks II Unlimited
  • Lecture 38 – Probabilistic Learning Unlimited
  • Lecture 39 – Natural Language Processing I Unlimited
  • Lecture 40 – Natural Language Processing II Unlimited

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