Artificial Intelligence NPTEL
Online Free Online Course by
World Mentoring Academy
Online
/ Free Online Course
Details
Description: 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,Game Playing : minimax, alpha-beta pruning. Knowledge and Reasoning : Building a Knowledge Base : Propositional logic, first order logic, situation calculus. Theorem Proving in First Order Logic. Planning, partial
order planning. Uncertain Knowledge and Reasoning, Probabilities, Bayesian Networks. Learning : Overview of different forms of learning, Learning Decision Trees, Neural Networks. Introduction to Natural Language Processing.
Resources: OpenCourseware from NPTEL (India), Sheridan College, MIT, UC Berkeley, Stanford & many other of the World's finest University's
Language: English
Units: 40
Lesson content
- Lec 1 Introduction to Artificial Intelligence
- Lec 2 Intelligent Agents
- Lec 3 State Space Search
- Lec 4 Uninformed Search
- Lec 5 Informed Search
- Lec 6 Informed Search - 2
- Lec 7 Two Players Games - I
- Lec 8 Two Players Games - II
- Lec 9 Constraint Satisfaction Problems - 1
- Lec 10 Constraint Satisfaction Problems 2
- Lec 11 Knowledge Representation and Logic
- Lec 12 Interface in Propositional Logic
- Lec 13 First Order Logic
- Lec 14 Reasoning Using First Order Logic
- Lec 15 Resolution in FOPL
- Lec 16 Rule Based System
- Lec 17 Rule Based Systems II
- Lec 18 Semantic Net
- Lec 19 Reasoning in Semantic Net
- Lec 20 Frames
- Lec 21 Planning - 1
- Lec 22 Planning - 2
- Lec 23 Planning - 3
- Lec 24 Planning - 4
- Lec 25 Rule Based Expart System
- Lec 26 Reasoning with Uncertainty - I
- Lec 27 Reasoning with Uncertainty - II
- Lec 28 Reasoning with Uncertainty III
- Lec 29 Reasoning with Uncertainty - IV
- Lec 30 Fuzzy Reasoning - I
- Lec 31 Fuzzy Reasoning - II
- Lec 32 Introduction to Learning - I
- Lec 33 Introduction to Learning - II
- Lec 34 Rule Induction and Decision Trees - I
- Lec 35 Rule Induction and Decision Trees - II
- Lec 36 Leavning Using neural Networks - I
- Lec 37 Learning Using Neural Networks - II
- Lec 38 Probabilistic Learning
- Lec 39 Natural Language Processing - I
- Lec 40 Natural Language Processing II
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