People Innovation Excellence


Learning Outcomes:

On successful completion of this Course, students will be able to: Describe what is AI and identify the concept of intelligent agent; Explain various intelligent search algorithms to solve problems; Explain how to use knowledge representation in reasoning purpose; Apply various techniques to an agent when acting under certainty; Apply various learning algorithms to solve the problems; Apply AI algorithms on various applications such as Game AI, Natural Language Processing, and Computer Vision.


  1. Introduction to Artificial Intelligence;
  2. Search Strategies;
  3. Local Search;
  4. Adversarial Search;
  5. Logical Agents;
  6. First-Order Logic;
  7. Fuzzy Systems;
  8. Quantifying Uncertainty I;
  9. Quantifying Uncertainty II;
  10. Probabilistic Reasoning;
  11. AI Application;
  12. Probabilistic Reasoning over Time;
  13. Project Proposal Presentation;
  14. Learning from Examples;
  15. Linear Regression and Classification;
  16. Introduction to Machine Learning;
  17. K-Nearest Neighbor;
  18. Artificial Neural Network;
  19. Support Vector Machine;
  20. Learning Probabilistic Models;
  21. Natural Language Processing;
  22. Natural Language for Communication;
  23. Introduction to Computer Vision;
  24. Project Presentation.


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