MATH-496: Computational linear algebraThis is an introductory course to the concentration of measure phenomenon - random functions that depend on many random variables tend to be often close to constant functions.
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
MGT-499: Statistics and data scienceThis class provides a hands-on introduction to statistics and data science, with a focus on causal inference, applications to sustainability issues using Python, and dissemination of scientific result
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
MGT-416: Causal inferenceStudents will learn the core concepts and techniques of network analysis with emphasis on causal inference. Theory and
application will be balanced, with students working directly with network data th
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-434: Lattice modelsLattice models consist of (typically random) objects living on a periodic graph. We will study some models that are mathematically interesting and representative of physical phenomena seen in the real
COM-417: Advanced probability and applicationsIn this course, various aspects of probability theory are considered. The first part is devoted to the main theorems in the field (law of large numbers, central limit theorem, concentration inequaliti