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, the 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)