This course (CS 365) unveils the core principles of intelligence in machines, from its historical roots to cutting-edge applications. It covers their theoretical underpinnings while providing opportunities to put various techniques into practice. Unravel the fundamental concepts of Neural Networks, Convolutional Neural Networks, and the Bayesian version of ML. You build your own AI through interactive labs, tackling real-world challenges. Prepare to shape the future of intelligent systems. This course contains theory and discussions: it is a course to read, learn about history, it contains topics to think, and to calculate. Find material for this course on official website.

Find this course in Moodle.

Bibliography and references

[1] Stuart J Russell and Peter Norvig. Artificial intelligence a modern ap-
proach. London, 2010. URL. This book has extra material in the following website http://aima.cs.berkeley.edu/ and this repository https://github.com/aimacode. Additionally, the version 4rth includes
this website with the exercises https://aimacode.github.io/aima-exercises/.

Extra material

[1] My github https://github.com/Earlham-College/CS365