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Syllabus
Introduction, Motivation of the course.
Problem Solving: Uninformed search, Informed search, local Search, Online search.
Knowledge and Reasoning: Propositional and Predicate Calculus, Semantic Nets, Frames, Scripts, Probabilistic Reasoning.
Learning: Introduction to machine learning paradigms: unsupervised, supervised, reinforcement learning, Naive Bayes, Decision Tree, Fundamental of Neural Networks and Deep Learning.
Evolutionary Computation: Genetic algorithms, Multi objective optimization, Differential Evolution, Particle Swarm and Ant Colony Optimization.
Application Topics: Introduction to NLP, Ethics and Bias in AI
Reference Books
- S. Russel and P. Norvig. Artificial Intelligence: A Modern Approach (Third Edition), Prentice Hall, 2009.
Artificial Intelligence: A Modern Approach (3rd Edition) (ucla.edu) - E. Rich and K. Knight, Artificial Intelligence, Addison Wesley, 1990
Artifical Inteliigence.pdf (mit.edu) - George Klir, U. St. Clair and B. Yuan, Fuzzy Set Theory: Foundations and Applications, Prentice Hall, 1997
- Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learnng, MIT Press, 2016
- Daphne Koller and Nir Friedman, Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009.
Classes
| Lecture # | Link to Class | Topic Covered | Remarks |
|---|---|---|---|
| 1 | Class 1: 29 July 2023 | ||
| 2 | Class 2: 29 July 2023 | ||
| 3 | Class 3: 31 July 2023 | ||
| 4 | Class 4: 5 Aug 2023 | ||
| 5 | Class 5: 5 Aug 2023 | ||
| 6 | Class 6: 7 Aug 2023 | ||
| 7 | Class 7: 12 Aug 2023 | ||
| 8 | Class 8: 12 Aug 2023 | ||
| 9 | Class 9: 14 Aug 2023 | ||
| 10 | Class 10: 28 Aug 2023 | Local Search Hill Climbing | |
| 11 | Weekend Class: 2 Sep 2023 | Hill Climbing | |
| 12 | Weekend Class: 2 Sep 2023 2nd Class | ||
| 13 | Class 11: 4 Sep 2023 | ||
| 14 | Weekend Class 9 Sep 2023 | ||
| 15 | Weekend Class 10 Sep 2023 | ||
| 16 | Class 12: 11 Sep 2023 | ||
| 17 | |||
| 18 | |||
| 19 | Weekend Class: 16 Sep 2023 | Laplace Smoothing | |
| 20 | |||
| 21 | |||
| 22 | |||
Topic wise Learning Material:
| Topic | Link | Remarks |
|---|---|---|
| Search BFS DFS A* | CS50’s Introduction to Artificial Intelligence | |
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