Machine learning is a sub-field of Artificial Intelligence that allows computers to learn from data, identify patterns and make predictions. As a fundamental building block of the Computational Thinking education at EPFL, Civil students will learn ML with ...
The goal of this course is twofold: (1) to introduce physiological basis, signal acquisition solutions (sensors) and state-of-the-art signal processing techniques, and (2) to propose concrete examples of applications for vital sign monitoring and diagnosis ...
With this course, the student will learn about advanced methods in transmission electron microscopy, especially what is the electron optical setup involved in the acquisition, and how to interpret the data. After the course, students will be able to unders ...
Ce cours est une introduction aux concepts fondamentaux de l'analyse vectorielle et de l'analyse complexe en vue de leur
utilisation dans d'autres cours et pour résoudre des problèmes pluridisciplinaires d'ingénierie scientifique. ...
"To be useful, helpful, of assistance to someone:" The "In Service of: Berre" studio
reflects on the architectural and territorial project as a form of public service. It explores how architecture and design tools can engage in spatial struggles in the con ...
The goal of the course is to introduce relativistic quantum field theory as the conceptual and mathematical framework describing fundamental interactions such as Quantum Electrodynamics. ...
We discuss a set of topics that are important for the understanding of modern data science but that are typically not taught in an introductory ML course. In particular we discuss fundamental ideas and techniques that come from probability, information the ...
The course covers several exact, approximate, and numerical methods to solve the time-dependent molecular Schrödinger equation, and applications including calculations of molecular electronic spectra. More advanced topics include introduction to the semicl ...