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 imple
CS-413: Computational photographyThe students will gain the theoretical knowledge in computational photography, which allows recording and processing a richer visual experience than traditional digital imaging. They will also execute
MICRO-330: SensorsPrincipes physiques et électronique utilisés dans les capteurs. Applications des capteurs.
EE-511: Sensors in medical instrumentationFundamental principles and methods used for physiological signal conditioning. Electrode, optical, resistive, capacitive, inductive, and piezoelectric sensor techniques used to detect and convert phys
AR-329: Constructing the view: built imagesWhat is meant by the term "image" as pictorial representation? How do we read, process and interpret images - and what premises can be derived from this for the conception and production of meaningful
ME-426: Micro/Nanomechanical devicesIn this course we will see an overview of the
exciting field of Micro and Nanomechanical systems. We will go over the dfferent scaling laws that dominate the critical parameters, how size affects mat
EE-440: Photonic systems and technologyThe physics of optical communication components and their applications to communication systems will be covered. The course is intended to present the operation principles of contemporary optical comm
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 practi
