Course

MSE-487: Mathematical methods for materials science

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

DH-406: Machine learning for DH

This course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and imple

EE-580: Introduction to the design of space mechanisms

Space environment is different from what we can experience on Earth, requiring specific design approaches in order to achieve reliable operations. Engineers must hence face new challenges stimulating

MATH-412: Statistical machine learning

A course on statistical machine learning for supervised and unsupervised learning

BIO-449: Understanding statistics and experimental design

This course is neither an introduction to the mathematics of statistics nor an introduction to a statistics program such as R. The aim of the course is to understand statistics from its experimental d

ME-273: Introduction to control of dynamical systems

Cours introductif à la commande des systèmes dynamiques. On part de quatre exemples concrets et on introduit au fur et à mesure un haut niveau d'abstraction permettant de résoudre de manière unifiée l

MICRO-301: Manufacturing technologies

This course gives an introduction to production methods and manufacturing technologies used in microengineering. The focus is given on the understanding of physical phenomena underlying the processes,

MGT-416: Causal inference

Students will learn the core concepts and techniques of network analysis with emphasis on causal inference. Theory and application will be balanced, with students working directly with network data th

MGT-484: Applied probability & stochastic processes

This course focuses on dynamic models of random phenomena, and in particular, the most popular classes of such models: Markov chains and Markov decision processes. We will also study applications in q

CS-526: Learning theory

Machine learning and data analysis are becoming increasingly central in many sciences and applications. This course concentrates on the theoretical underpinnings of machine learning.

ME-451: Advanced energetics

Methods for the rational use and conversion of energy in industrial processes : how to analyse the energy usage, calculate the heat recovery by pinch analysis, define heat exchanger network, integrate