In this course, we have learned about the fundamentals of AI and applications of AI in lesson on principles of AI, then we wrote a Python code to model a Tic-Tac-Toe game.

In the lesson AI with Search Techniques and Games, we solved the Tic-Tac-Toe game with game AI tools and search techniques. We learned about the search algorithms of Breadth First Search and Depth First Search. The A* algorithm helped students model a pathfinding problem. The lesson was concluded with modeling multiplayer games.

In the next couple of lessons, we learned about supervised learning using regression and classification. These lessons included data preprocessing, train-test splitting, and models that were used in several real-life scenarios. Linear regression, polynomial regression, and Support Vector Machines all came in handy when it came to predicting stock data. Classification was performed using the k-nearest neighbor and Support Vector classifiers. Several activities helped students apply the basics...