NOC:Artificial Intelligence: Concepts and Techniques

Lecture 1 - Course overview and Introduction

Lecture 2 - History and Applications of AI

Lecture 3 - Agents and Environment

Lecture 4 - General Problem Solving

Lecture 5 - Introduction to Search Strategies

Lecture 6 - Uninformed Search Strategies - I

Lecture 7 - Uninformed Search Strategies - II

Lecture 8 - Informed Search Strategies - I

Lecture 9 - Informed Search Strategies - II

Lecture 10 - Adversarial or Game-Playing Search

Lecture 11 - Game-Playing Search

Lecture 12 - Introduction to Genetic Algorithms

Lecture 13 - GA Operators

Lecture 14 - Genetic Programming

Lecture 15 - Knowledge-Base Agents

Lecture 16 - Proposotional Logic

Lecture 17 - Predicate Logic - 1

Lecture 18 - Predicate Logic - 2

Lecture 19 - Inference in Predicate Logic

Lecture 20 - Inference in First Order Logic

Lecture 21 - Introduction to Expert Systems

Lecture 22 - Applications of Expert Systems

Lecture 23 - Introduction to Planning

Lecture 24 - Planning Graph

Lecture 25 - Planning and Scheduling

Lecture 26 - Knowledge Representation

Lecture 27 - Non Monotonic Reasoning

Lecture 28 - Representation Schemes - 1

Lecture 29 - Representation Schemes - 2

Lecture 30 - Uncertanity in Knowledge Representation

Lecture 31 - Bayesian Network

Lecture 32 - Dynamic belief networks (DBN)

Lecture 33 - Utility Theory

Lecture 34 - Decision Theory - 1

Lecture 35 - Decision Theory - 2

Lecture 36 - Introduction to Learning

Lecture 37 - Learning Algorithms

Lecture 38 - Learning Algorithms

Lecture 39 - Ensemble Learning

Lecture 40 - Introduction to Neural Networks

Lecture 41 - Multilayer Perceptron Neural network

Lecture 42 - Hypothesis Learning

Lecture 43 - Practical Session - 1

Lecture 44 - Practical Session - 2

Lecture 45 - Introduction to deep learning

Lecture 46 - Datasets for DL

Lecture 47 - CNN and introduction to RNN

Lecture 48 - RNN and LSTMs

Lecture 49 - Practical Session - 3

Lecture 50 - Practical Session - 4

Lecture 51 - Practical Session - 5

Lecture 52 - Generative AI

Lecture 53 - Fuzzy Sets and Systems

Lecture 54 - Fuzzification and Defuzzification methods

Lecture 55 - Natural Language Processing

Lecture 56 - Ethics in AI

Lecture 57 - Swarm Intelligence

Lecture 58 - Multi agent systems