Artificial Intelligence (AI)

Description

In this course, you will learn:

• Introduction to artificial intelligence (AI) and intelligent agents, as well as AI's history.
• Creating clever robots (search, games, logic, constraint satisfaction problems).
• Algorithms for Machine Learning
• (Natural Language Processing, Robotics/Vision) AI applications
• Python programming is used to solve real-world AI difficulties.

Syllabus:

1. Introduction to AI, history of AI, course logistics
2. Intelligent agents, uninformed search
3. Heuristic search, A algorithm
4. Adversarial search, games
5. Constraint Satisfaction Problems
6. Machine Learning: Basic concepts, linear models, perceptron, K nearest neighbors
7. Machine Learning: advanced models, neural networks, SVMs, decision trees and unsupervised learning
8. Markov decision processes and reinforcement learning
9. Logical Agent, propositional logic and first order logic
10. AI applications (NLP)
11. AI applications (Vision/Robotics)
12. Review and Conclusion