COM-406: Foundations of Data ScienceWe discuss a set of topics that are important for the understanding of modern data science but that are typically not taught in an introductory ML course. In particular we discuss fundamental ideas an
BIO-373: Genetics and genomicsThe theoretical part of this course covers classical genetics and contemporary genomics. Because bioinformatics has become important for genomic research, the course also includes practical applicatio
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
BIO-410: Bioimage informaticsThe course provides a comprehensive overview of methods, algorithms, and computer tools used in bioimage analysis. It exposes fundamental concepts and practical computer solutions to extract quantitat
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
CS-438: Decentralized systems engineeringA decentralized system is one that works when no single party is in charge or fully trusted. This course teaches decentralized systems principles while guiding students through the engineering of thei