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 ...
ENV-471: Environmental economicsIntroduction to economic analysis applied to environmental issues: all the necessary basic concepts, including cost-benefit analysis, for environmental policy making and its instruments (examples: climate, waste, mobility). Introduction to financial calcul ...
ENV-367: Environmental and construction lawCe cours donne aux étudiant-e-s les connaissances de base nécessaires pour comprendre les dimensions juridiques de leur activité professionnelle concernant l'aménagement du territoire et la protection de l'environnement. Il les sensibilise aux questions ju ...
MGT-454: Principles of microeconomicsThe course allows students to get familiarized with the basic tools and concepts of modern microeconomic analysis. Based on graphical reasoning and analytical calculus, it constantly links to real economic issues. ...
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. ...
ENG-410: Energy supply, economics and transitionThis course examines energy systems from various angles: available resources, how they can be combined or substituted, their private and social costs, whether they can meet the energy demand, and how the transition to a renewable energy system can be foste ...
CS-467: AI for global healthThis course teaches students to design, build and rigorously evaluate trustworthy, representative and contextually appropriate AI systems for high-stakes decision-making in global health and humanitarian response.
CIVIL-486: Integrated decision-making for buildingsThis course addresses low-carbon buildings as a problem of integrated decision-making. Through cases, debates, and decision exercises, students learn to justify decisions at the energy-material nexus, navigating trade-offs, uncertainty, and competing technical, economic, and societal objectives.
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 ...
ENG-209: Data science for engineers with PythonCe cours propose une immersion progressive et complète dans le domaine de la Data Science à travers le langage Python. Il guide les étudiants depuis la manipulation de données brutes jusqu'à la modélisation et l'extraction de connaissances utiles à partir ...
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-451: Distributed algorithmsComputing is nowadays distributed over several machines, in a local IP-like network, a cloud or a P2P network. Failures are common and computations need to proceed despite partial failures of machines or communication links. This course will study the fo ...
HEC-504: Sustainable choice modelsWith sustainability playing an increasingly important role in consumer behavior, businesses face the challenge of promoting more responsible choices. This course equips students with the tools to analyze decision-making and design strategies that nudge consumers toward sustainability.
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-461: Foundation models and generative AIThis course covers the principles, architectures, and applications of foundation models and generative AI, including generative methods, tokenization, multi-modal learning, adaptation, prompting, and their use in reasoning, decision-making, and scientific ...
