CS-213: Human-computer interactionLa discipline de l'Interaction Homme-Machine (ou HCI : Human-Computer Interaction) vise à systématiquement placer le facteur humain dans la conception de systèmes interactifs. ...
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 their own decentralized system featuring messaging, file sha ...
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 and techniques that come from probability, information the ...
MICRO-436: Computational motor controlThe course gives (1) a review of different types of numerical models of control of locomotion and movement in animals, from fish to humans, (2) a presentation of different techniques for designing models, and (3) an analysis of the use and testing of those ...
COM-490: Large-scale data science for real-world dataThis hands-on course covers tools and methods used by data scientists, from researching solutions to scaling prototypes on Spark clusters. Students engage with the full data engineering and data science pipeline, from data acquisition to extracting insight ...
HUM-432: How people learn: Designing Learning Tools IThe students will understand the cognitive and social factors which affect learning - particularly in science and engineering. They will be able to use social research techniques as part of the design process to understand end users. ...
CS-214: Software constructionLearn how to design and implement reliable, maintainable, and efficient software using a mix of programming skills (declarative style, higher-order functions, inductive types, parallelism) and
fundamental software construction concepts (reusability, abstr ...
BIO-512: Digital epidemiologyEpidemiology is foundational to medicine and public health. This course starts with the key principles of classical epidemiology, progressing through computational modeling techniques, and concluding with the digital approaches of today. Students will also ...
MICRO-455: Machine learning IReal-world engineering applications must cope with a large dataset of dynamic variables, which cannot be well approximated by classical or deterministic models. This course gives an overview of methods from Machine Learning for the analysis of non-linear, highly noisy and multi dimensional data
CS-401: Applied data analysisThis course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world (pandas, scikit-learn, Spark, etc.) ...
PHYS-452: Radiation detectionThe course presents the detection of ionizing radiation in the keV and MeV energy ranges. Physical processes of radiation/matter interaction are introduced. All steps of detection are covered, as well as detectors, instrumentations and measurements methods ...
CS-523: Advanced topics on privacy enhancing technologiesThis advanced course will provide students with the knowledge to tackle the design of privacy-preserving ICT systems. Students will learn about existing technologies to prect privacy, and how to evaluate the protection they provide. ...
CS-101: Advanced information, computation, communication IDiscrete mathematics is a discipline with applications to almost all areas of study. It provides a set of indispensable tools to computer science in particular. This course reviews (familiar) topics as diverse as mathematical reasoning, combinatorics, disc ...
ME-403: Applied mechanical designStudents will be exposed to hands-on design problems throughout the term. They will acquire methodologies to (1) address open ended engineering problems, (2) cultivate creativity, (3) support decision making and (4) develop problem solving abilities. ...
CS-411: Digital educationThis course addresses the relationship between specific technological features and the learners' cognitive processes. It also covers the methods and results of empirical studies: do student actually learn due to technologies? In fall 2025, P. Dillenbourg w ...
MATH-414: Stochastic simulationThe student who follows this course will get acquainted with computational tools used to analyze systems with uncertainty arising in engineering, physics, chemistry, and economics. Focus will be on sampling methods as Monte Carlo, quasi Monte Carlo, Mark ...
