This course introduces the fundamental concepts of Artificial Intelligence and explains how intelligent systems solve problems and learn from data. It is designed for beginners who want to understand the core ideas behind AI.
The course begins with an introduction to the scope of Artificial Intelligence and how AI is used to solve complex problems. It then explores reasoning techniques such as goal trees and rule-based expert systems, which help computers make logical decisions.
Next, the course explains search algorithms that allow AI systems to explore possible solutions. You will learn about methods such as depth-first search, hill climbing, beam search, branch and bound, and the A* algorithm. The course also covers game-playing strategies including the minimax algorithm and alpha-beta pruning.
Another important part of the course focuses on constraint satisfaction problems and how AI systems interpret visual information. Topics include interpreting line drawings, domain reduction, and visual object recognition.
Finally, the course introduces basic machine learning techniques. You will learn how computers learn from data using methods such as nearest neighbors and identification trees.
By the end of the course, learners will understand the main techniques used in AI systems and how they are applied in real-world problem solving.
