Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Graph
Search

Course

EE-802: Mathematical guarantees of data-driven control

Summary

Students learn about advanced topics in data-driven control theory. Students also learn to present and analyze scientific work.

Lectures

Instructors

Official source

https://edu.epfl.ch/coursebook/en/mathematical-guarantees-of-data-driven-control-EE-802

Moodle Page

http://go.epfl.ch/EE-802

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Summary

Students learn about advanced topics in data-driven control theory. Students also learn to present and analyze scientific work.

Lectures

Instructors

Official source

https://edu.epfl.ch/coursebook/en/mathematical-guarantees-of-data-driven-control-EE-802

Moodle Page

http://go.epfl.ch/EE-802

About this result

Related courses (30)

EE-556: Mathematics of data: from theory to computation

This course provides an overview of key advances in continuous optimization and statistical analysis for machine learning. We review recent learning formulations and models as well as their guarantees

PHYS-467: Machine learning for physicists

Machine 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. ...

CS-401: Applied data analysis

This course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world (pandas, scikit-learn, Spark, etc.) ...

CS-101: Advanced information, computation, communication I

Discrete 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 ...

COM-406: Foundations of Data Science

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 ...