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.) ...
CS-421: Machine learning for behavioral dataComputer environments such as educational games, interactive simulations, and web services provide large amounts of data, which can be analyzed and serve as a basis for adaptation. This course will cover the core methods of user modeling and personalizatio ...
CS-433: Machine learningMachine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...
AR-301(bh): Théorie et critique du projet BA5 (Weyell Zipse)The Systemic Type explores architecture as an open system, adapting to changing environmental, social and programmatic conditions. Typology is understood not as a fixed model, but as a set of relationships between structure and space, inside and outside, climate and material, permanence and change.
AR-302(bh): Théorie et critique du projet BA6 (Weyell Zipse)The Systemic Type explores architecture as an open system, adapting to changing environmental, social and programmatic conditions. Typology is understood not as a fixed model, but as a set of relationships between structure and space, inside and outside, climate and material, permanence and change.
AR-401(bh): Théorie et critique du projet MA1 (Weyell Zipse)The Systemic Type explores architecture as an open system, adapting to changing environmental, social and programmatic conditions. Typology is understood not as a fixed model, but as a set of relationships between structure and space, inside and outside, climate and material, permanence and change.
AR-402(bh): Théorie et critique du projet MA2 (Weyell Zipse)The Systemic Type explores architecture as an open system, adapting to changing environmental, social and programmatic conditions. Typology is understood not as a fixed model, but as a set of relationships between structure and space, inside and outside, climate and material, permanence and change.
MSE-213: Probability and statistics for materials scienceThe course establishes the concepts of statistical analysis, probability theory, and data analysis. This includes standard statistical tests, correlation analysis and experimental design. It introduces computational statistical methods to analyse large dat ...
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 ...
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-131: Probabilités et statistiqueLe cours présente les notions de base de la théorie des probabilités et de l'inférence statistique. L'accent est mis sur les concepts principaux ainsi que les méthodes les plus utilisées. ...
ME-419: Production managementProduction management deals with producing goods sustainably at the right time, quantity, and quality with the minimum cost. This course equips students with practical skills and tools for effectively managing demand, supply, and implementing advanced anal ...
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.
FIN-407: Machine learning in financeThis course aims to give an introduction to the application of machine learning to finance, focusing on the problems of portfolio optimization, return prediction, and textual analysis. A particular focus will be on deep learning and the practical details o ...
ME-467: TurbulenceThis course provides an introduction to the physical phenomenon of turbulence, its probabilistic description and modeling approaches including RANS and LES. Students are equipped with the basic knowledge to tackle complex flow problems in science and engin ...
ME-422: Multivariable controlThis course covers methods for the analysis and control of systems with multiple inputs and outputs, which are ubiquitous in modern technology and industry. Special emphasis will be placed on discrete-time systems due to their relevance to digital and embe ...
