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.
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 machin
ME-251: Thermodynamics and energetics IThe course introduces the basic concepts of thermodynamics and heat transfer, and thermodynamic properties of matter and their calculation. The students will master the concepts of heat, mass, and mom
BIO-693: Bioinformatic Analysis of RNA-sequencingThis course will take place from 2nd to 6th June 2025 in room AAC 1 37.
It introduces the workflows and techniques that are used for the analysis of bulk and single-cell RNA-seq data. It empowers stu
MATH-251(a): Numerical analysisThis course presents numerical methods for the solution of mathematical problems such as systems of linear and non-linear equations, functions approximation, integration and differentiation, and diffe
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
ENV-222: Soil sciencesLe cours est une introduction aux Sciences du sol. Il a pour but de présenter les principales caractéristiques, propriétés et fonctions des sols. Il fait appel à des notions théoriques mais également
