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.
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 pr
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.
EE-411: Fundamentals of inference and learningThis is an introductory course in the theory of statistics, inference, and machine learning, with an emphasis on theoretical understanding & practical exercises. The course will combine, and alternat
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 m
EE-594: Smart sensors for IoTThis lecture provides insights in the design and technologies of Internet-of-Things sensor nodes, with focus on low power technologies. The lectures alternate every two weeks between sensing technolog
CH-412: Frontiers in chemical biologyChemical biology is a key discipline in biomedical research for drug discovery, synthetic biology and protein functional annotation. We will give a broad perspective of the field ranging from seminal
BIOENG-404: Analysis and modelling of locomotionThe lecture presents an overview of the state of the art in the analysis and modeling of human locomotion and the underlying motor circuits. Multiple aspects are considered including neurophysiology,
