MGT-484: Applied probability & stochastic processesThis course focuses on dynamic models of random phenomena, and in particular, the most popular classes of such models: Markov chains and Markov decision processes. We will also study applications in queuing theory, finance, project management, etc. ...
EE-568: Reinforcement learningThis course describes theory and methods for Reinforcement Learning (RL), which revolves around decision making under uncertainty. The course covers classic algorithms in RL as well as recent algorithms under the lens of contemporary optimization. ...
FIN-415: Probability and stochastic calculusThis course gives an introduction to probability theory and stochastic calculus in discrete and continuous time. The fundamental notions and techniques introduced in this course have many applications in finance, for example for option pricing, risk mana ...
COM-309: Introduction to quantum information processingInformation is processed in physical devices. In the quantum regime the concept of classical bit is replaced by the quantum bit. We introduce quantum principles, and then quantum communications, key distribution, quantum entropy, and spin dynamics. No prio ...
PHYS-454: Quantum optics and quantum informationThis lecture describes advanced concepts and applications of quantum optics. It emphasizes the connection with ongoing research, and with the fast growing field of quantum technologies. The topics cover some aspects of quantum information processing, quant ...
MATH-414: Stochastic simulationThe student who follows this course will get acquainted with computational tools used to analyze systems with uncertainty arising in engineering, physics, chemistry, and economics. Focus will be on sampling methods as Monte Carlo, quasi Monte Carlo, Mark ...
PHYS-441: Statistical physics of biomacromoleculesBiological macromolecules such as DNA, RNA, proteins and cytoskeletal filaments are polymers. As such, they share a set of properties that are common to any polymer, which are the focus of this course. Details about the protein folding problem will be cove ...
CS-450: Algorithms IIA first graduate course in algorithms, this course assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design, while building a repertory of basic algorithmic solutions to problems in many ...
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 practised. ...
MATH-517: Statistical computation and visualisationThe course will provide the opportunity to tackle real world problems requiring advanced computational skills and visualisation techniques to complement statistical thinking. Students will practice proposing efficient solutions, and effectively communicati ...
EE-554: Automatic speech processingThe goal of this course is to provide the students with the main formalisms, models and algorithms required for the implementation of advanced speech processing applications (involving, among others, speech coding, speech analysis/synthesis, and speech rec ...
PHYS-339: Advanced computational physicsThe course covers dense/sparse linear algebra, variational methods in quantum mechanics, and Monte Carlo techniques. Students implement algorithms for complex physical problems. Combines theory with coding exercises. Prepares for research in computational ...
COM-621: Advanced Topics in Information TheoryThe class will focus on information-theoretic progress of the last decade. Topics include: Network Information Theory ; Information Measures: definitions, properties, and applications to probabilistic models. ...
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 in python using jupyter notebooks. ...
HUM-274: Musical theory and creativityThis course provides an introduction into music theory and analysis, composition, and creativity, and combines theoretical teaching with hands-on practical exercises and music making. ...
ENG-639: Dynamic programming and optimal controlThis course provides an introduction to stochastic optimal control and dynamic programming (DP), with a variety of engineering
applications. The course focuses on the DP principle of optimality, and its utility in deriving and approximating solutions to an ...
PHYS-744: Advanced Topics in Quantum Sciences and TechnologiesThis course provides an in-depth treatment of the latest experimental and theoretical topics in quantum sciences and technologies, including for example quantum sensing, quantum optics, cold atoms, theory of quantum measurements and open dissipative quantu ...
