MATH-410: Riemann surfacesThis course is an introduction to the theory of Riemann surfaces. Riemann surfaces naturally appear is mathematics in many different ways: as a result of analytic continuation, as quotients of complex domains under discontinuous group actions, as algebraic ...
CS-463: Hardware-software co-designThis course offers a deep dive into the architecture and programming of modern computing systems, moving beyond general-purpose CPUs to explore how hardware and software are co-designed for maximum efficiency.
CS-101: Advanced information, computation, communication IDiscrete mathematics is a discipline with applications to almost all areas of study. It provides a set of indispensable tools to computer science in particular. This course reviews (familiar) topics as diverse as mathematical reasoning, combinatorics, disc ...
ME-326: Control systems and discrete-time controlCe cours inclut la modélisation et l'analyse de systèmes dynamiques, l'introduction des principes de base et l'analyse de systèmes en rétroaction, la synthèse de régulateurs dans le domain fréquentiel et dans l'espace d'état, et la commande de systèmes dis ...
MICRO-435: Quantum and nanocomputingThe course teaches non von-Neumann architectures. The first part of the course deals with quantum computing, sensing, and communications. The second focuses on field-coupled and conduction-based nanocomputing, in-memory and molecular computing, cellular au ...
EE-566: Adaptation and learningIn this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.
COM-490: Large-scale data science for real-world dataThis hands-on course covers tools and methods used by data scientists, from researching solutions to scaling prototypes on Spark clusters. Students engage with the full data engineering and data science pipeline, from data acquisition to extracting insight ...
CS-448: Sublinear algorithmsIn this course we will define rigorous mathematical models for computing on large datasets, cover main algorithmic techniques that have been developed for sublinear (e.g. faster than linear time) data processing. We will also discuss limitations inherent t ...
QUANT-400: Introduction to quantum science and technologyA broad view of the diverse aspects of the field is provided: quantum physics, communication, quantum computation, simulation of physical systems, physics of qubit platforms, hardware technologies. Students will grasp the field as a whole and better orient ...
PHYS-464: Solid state systems for quantum informationThis course will give an overview of the experimental state of the art of quantum technology for Quantum Information Processing (QIP). We will explore some of the most promising approaches for realizing quantum hardware and critically assess each approach' ...
MATH-611: Scientific programming for EngineersThe students will acquire a solid knowledge on the processes necessary to design, write and use scientific software. Software design techniques will be used to program a multi-usage particles code, aiming at providing the link between algorithmic/complexit ...
COM-401: Cryptography and securityThis course introduces the basics of cryptography. We review several types of cryptographic primitives, when it is safe to use them and how to select the appropriate security parameters. We detail how they work and sketch how they can be implemented. ...
CS-423: Distributed information systemsThis course introduces the foundations of information retrieval, data mining and knowledge bases, which constitute the foundations of today's Web-based distributed information systems. ...
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 implement methods to analyze diverse data types, such as imag ...
CS-206: Parallelism and concurrencyCourse no longer offered for new students; this edition is only a make-up course for those who repeated the year. Please log in with EPFL credentials and consult the mediaspace link below for course videos. ...
CS-233(a): Introduction to machine learning (BA3)Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...
MSE-806: Spin-based devices for neuromorphic computingThe course entails a 5-days-program with lectures and exercises about spin-based computing and novel spin texture-based computing devices. An additional round table discussion and journal club session provide further knowledge about recent trends and chall ...
