Hi! ๐
After a long wait, I can finally announce the project I've been hinting at for the past year! ๐
"Game AI" is an online course designed for game developers and programmers who are keen to learn how Artificial Intelligence is applied in videogames. It focuses on Classical AI, covering popular techniques such as Behaviour Trees, Pathfinding, Goal-Oriented Action Planning, Evolutionary Computation, and even Neural Networks! The aim of this course is not just to teach you how to use those techniques, but to understand how and why they work in the first place.

The course counts overs 20 hours of content, divided between 12 chapters, focusing on as many topics and techniques. โGame AIโ is designed like a buffet: each chapter is self-contained, so that you can skip the ones that are not relevant to you, and focus on what you really need.
๐ค 01: Introduction
๐ 02: History of AI
๐ 03: Finite State Machines
๐ณ 04: Behaviour Trees
๐บ๏ธ 05: Pathfinding
๐ 06: Steering Behaviours
๐ฆ 07: Emergent Behaviours
๐ 08: Utility Theory
๐ 09: Planning
๐ 10: Tree Search
๐งฌ 11: Evolution
๐ง 12: Neural Networks

All students also have access to a large number of C# libraries, designed to perform most of the AI techniques covered in the course. They are fully compatible with Unity, and can be used for free in your games and projects.
The course focuses on both theory and practice, with two practical assignments challenging students to create AIs for popular games, such as Snake and Tetris.
The course is available on Thinkific, one of the leading platforms for online courses, at the following address:
https://alanzucconi.thinkific.com/courses/game-ai
If you want to learn more about the course content, including a free preview, you can use this page:
https://www.alanzucconi.com/courses/game-ai/
And if the course is not what you expected, you can get a refund within 14 days!

YES, YOU CAN! ๐ This course would have not been possible without the constant support of people like you! All current patrons will receive a follow-up message with a discount code proportional to their tier! โค๏ธ
Thank you again for your patient support during the past year! And I hope you'll enjoy the new content that's coming! ๐
๐ง๐ป