This course focuses on the intersection of machine learning and mechanism design. It explores how incentives shape the behavior of agents in Machine Learning (ML) environments and how to design algorithms that align incentives with desirable system outcomes. The course aims to discuss how to apply the tools of game theory and mechanism design to problems in ML, such as designing incentive-compatible learning algorithms, managing strategic agents, and optimizing decision-making processes in multi-agent systemsÂ