EE-311: Fundamentals of machine learningCe cours présente une vue générale des techniques d'apprentissage automatique, passant en revue les algorithmes, le formalisme théorique et les protocoles expérimentaux.
ME-390: Foundations of artificial intelligenceThis course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanica
ME-419: Production managementProduction management deals with producing goods sustainably at the right time, quantity, and quality with the minimum cost. This course equips students with practical skills and tools for effectively
MSE-305: Introduction to atomic-scale modelingThis course provides an introduction to the modeling of matter at the atomic scale, using interactive Jupyter notebooks to see several of the core concepts of materials science in action.
ENG-466: Distributed intelligent systemsThe goal of this course is to provide methods and tools for modeling distributed intelligent systems as well as designing and optimizing coordination strategies. The course is a well-balanced mixture
CS-233(a): Introduction to machine learning (BA3)Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analy
FIN-418: Machine learning for financeThis course is introduces machine learning techniques for financial applications in algorithmic trading, derivatives pricing, model calibration, hedging, and risk management. The course format is hand
