This assignment allows students to gain experience with AI game-playing algorithms, implementing minimax and alpha-beta pruning and designing a utility function for measuring game states. The assignment uses Connect Four, a relatively simple fully-observable and deterministic game that students are likely to have seen before. Students are responsible only for developing an agent to play the game; the game itself is already implemented and given as part of the student-facing materials. The assignment breaks down the requirements for the two algorithms into smaller chunks in order to make the whole assignment more approachable. We also provide code for Tic-Tac-Toe so that students can apply their code for minimax and alpha-beta pruning to a simpler game where sub-optimal moves will be more obvious, indicating potential bugs in their implementation. The assignment allows for a tournament to be played among all student submissions, potentially awarding extra credit to the winner of the class tournament.