MICRO-428: MetrologyThe course deals with the concept of measuring in different domains, particularly in the electrical, optical, and microscale domains. The course will end with a perspective on quantum measurements, wh
EE-613: Machine Learning for EngineersThe objective of this course is to give an overview of machine learning techniques used for real-world applications, and to teach how to implement and use them in practice. Laboratories will be done i
PHYS-442: Modeling and design of experimentsIn the academic or industrial world, to optimize a system, it is necessary to establish strategies for the experimental approach. The DOE allows you to choose the best set of measurement points to min
MATH-330: Martingales and Brownian motionIntroduction to the theory of discrete-time martingales including, in particular, the convergence and stopping time theorems. Application to branching processes. Introduction to Brownian motion and st
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 co
CS-502: Deep learning in biomedicineDeep learning offers potential to transform biomedical research. In this course, we will cover recent deep learning methods and learn how to apply these methods to problems in biomedical domain.
MICRO-390: Light, liquids and interfacesThis course provides an overview of relevant interactions in liquids, combining thermodynamics, statistical physics and pair potetnials. Water and aqueos systm,es will be considered in detail. Optical
MATH-602: Inference on graphsThe class covers topics related to statistical inference and algorithms on graphs: basic random graphs concepts, thresholds, subgraph containment (planted clique), connectivity, broadcasting on trees,
