MATH-413: Statistics for data scienceStatistics lies at the foundation of data science, providing a unifying theoretical and methodological backbone for the diverse tasks enountered in this emerging field. This course rigorously develops
MATH-562: Statistical inferenceInference from the particular to the general based on probability models is central to the statistical method. This course gives a graduate-level account of the main ideas of statistical inference.
HUM-375: PrototypingLe cours réunit des étudiant·e·s de l'EPFL et de l'UNIL au travers d'une approche de design exploratoire et itérative. Les étudiant·e·s identifient un besoin ou une problématique de société et propose
CS-233(a): Introduction to machine learning (BA3)Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analy
MGT-529: Data science and machine learning IIThis class discusses advanced data science and machine learning (ML) topics: Recommender Systems, Graph Analytics, and Deep Learning, Big Data, Data Clouds, APIs, Clustering. The course uses the Wol
EE-714: Nonlinear signal modeling and predictionThe literature on nonlinear signal processing has exploded, and it becomes more and more difficult to identify the most useful approaches for specific contexts. This course presents promising developm
MATH-425: Spatial statisticsIn this course we will focus on stochastic approaches for modelling phenomena taking place in multivariate spaces. Our main focus will be on random field models and on statistical methods for model-ba