A Stanford course by Michael Genesereth on general game playing, where students build agents that play arbitrary games described in a formal logic-based game language. It covers game-tree search and related game AI techniques.

Commenters point to it as close to what the asker wants, a hands-on course on building game-playing AI such as a chess engine.

What commenters said (1)

1. Recommendspigscantfly2020in “Ask HN: What are the best advanced computer science courses online?”

   I would check out Michael Genesereth's course on general game playing [1] -- I don't remember if we specifically implemented a chess engine, but it's more or less exactly what you're looking for. Once you've mastered that, I'd move on to Mykel Kochenderfer's series on decision making under uncertainty [2], which extends to more state of the art approaches to the problem (ie. MCTS + deep Q learning + better encoders, which is basically what got us AlphaGo, AlphaStar, Atari agents, etc.). Once you've got that down (or before), you should start reading whitepapers.

   Genesereth and Kochenderfer also have books on the subject; Kochenderfer's is extremely good (I haven't read all of Genesereth's).

   [1] http://ggp.stanford.edu/

   [2] https://web.stanford.edu/class/aa228/cgi-bin/wp/ and https://web.stanford.edu/class/aa229/cgi-bin/wp/

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