Engineering in Computer Science and Artificial Intelligence

General outcomes: The course will present a broad survey of topics at the interface of computer science, data science, and economics, emphasizing efficiency, robustness, and application to emerging online markets. It will introduce the principles of algorithmic game theory and mechanism design, algorithmic market design, as well as machine learning in games and markets. It will demonstrate applications to case studies in Web search and advertising, network economics, Data, cryptocurrency, and AI markets. Specific outcomes: Knowledge and understanding: The algorithmic and mathematical economics principles underlying the design and the operation of efficient and robust online markets. The application of these principles in concrete examples of online markets. Applying knowledge and understanding: Being able to design and analyze algorithms for concrete online market applications with respect to the requirements of efficiency and robustness. Making judgements: Being able to evaluate the quality of an algorithm for online market applications, discriminating the modeling aspects from those related to algorithmic and system implementation. Communication skills: Ability to communicate and share the modeling choices and system requirements, as well as the results of the analysis of the efficiency of online market algorithms. Learning skills: The course stimulates the students to acquire learning skills at the crossroads of computer science, economics, and digital market applications, including the different languages used in these fields.