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 ...
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. ...
EE-566: Adaptation and learningIn this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.
PHYS-512: Statistical physics of computationThe students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and machine learning. ...
LEARN-601: Theoretical Foundations of Learning Sciences 2How do people learn and how can we support learning? This is part 2 of a two-part course that provides an overview of major theoretical perspectives that attempt to describe how learning works, and serves as an introduction to interpreting education as a m ...
HUM-279: Learning and collaboration in projectsThis course addresses the theoretical and practical basis of learning and how to facilitate learning through projects. Active exploration of models, contexts and tools used in project-based learning will help you to develop cognitive and collaboration skil ...
LEARN-600: Theoretical Foundations of Learning Sciences 1How do people learn and how can we support learning? This is part 1 of a two-part course that provides an overview of major theoretical perspectives that attempt to describe how learning works, and serves as an introduction to interpreting education as a m ...
CS-526: Learning theoryMachine learning and data analysis are becoming increasingly central in many sciences and applications. This course concentrates on the theoretical underpinnings of machine learning. ...
HUM-433: How people learn: Designing Learning Tools IIThe 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. ...
PHYS-754: Lecture series on scientific machine learningThis lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way. We will learn on examples how this is influencing the v ...
HUM-496: Comment enseigner la durabilité IIDans ce projet de groupe, explorez les pratiques pédagogiques dans un cours de durabilité. L'observation, la formulation de problèmes, la préparation en groupe, et la réflexion sur l'enseignement de la durabilité, vous aideront à développer des stratégies ...
HUM-490: Médiation scientifique ICet enseignement est une introduction à la théorie et la pratique de la médiation scientifique.
Cette année, ce cours aboutira à la création et l'animation d'un atelier pédagogique et interactif avec un groupe de jeunes. ...
PHYS-467: Machine learning for physicistsMachine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised. ...
BIO-369: Randomness and information in biological dataBiology is becoming more and more a data science, as illustrated by the explosion of available genome sequences. This course aims to show how we can make sense of such data and harness it in order to understand biological processes in a quantitative way. ...
BIO-480: Neuroscience: from molecular mechanisms to diseaseThe goal of the course is to guide students through the essential aspects of molecular neuroscience and neurodegenerative diseases. The student will gain the ability to dissect the molecular basis of disease in the nervous system in order to begin to under ...
AR-201(m): Théorie et critique du projet BA3 (Taillieu)A house is the simple topic of this studio. A matter of simple complexity. Learning about a house is learning about
architecture. The first part of the year is about learning about a house. The second part is about making your house. ...
AR-202(m): Théorie et critique du projet BA4 (Taillieu)A house is the simple topic of this studio. A matter of simple complexity. Learning about a house is learning about
architecture. The first part of the year is about learning about a house. The second part is about making your house. ...
DH-406: Machine learning for DHThis 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 implement methods to analyze diverse data types, such as imag ...
