263-5051-00L  AI Center Projects in Machine Learning Research

SemesterFrühjahrssemester 2022
DozierendeA. Ilic, M. El-Assady, F. Engelmann, T. Kontogianni, A. Marx, G. Ramponi, A. Sanyal, M. Sorbaro Sindaci
Periodizitätjährlich wiederkehrende Veranstaltung
KommentarNumber of participants limited to 50.

Last cancellation/deregistration date for this ungraded semester performance: Friday, 18 March 2022! Please note that after that date no deregistration will be accepted and the course will be considered as "fail".


263-5051-00 VAI Center Projects in Machine Learning Research2 Std.
Mi16:15-18:00HG D 5.2 »
A. Ilic, M. El-Assady, F. Engelmann, T. Kontogianni, A. Marx, G. Ramponi, A. Sanyal, M. Sorbaro Sindaci
263-5051-00 AAI Center Projects in Machine Learning Research1 Std.A. Ilic, M. El-Assady, F. Engelmann, T. Kontogianni, A. Marx, G. Ramponi, A. Sanyal, M. Sorbaro Sindaci


KurzbeschreibungThe course will give students an overview of selected topics in advanced machine learning that are currently subjects of active research. The course concludes with a final project.
LernzielThe overall objective is to give students a concrete idea of what working in contemporary machine learning research is like and inform them about current research performed at ETH.

In this course, students will be able to get an overview of current research topics in different specialized areas. Each topic is accompanied by small hands-on exercises that prepare for the final project. In the final project, students will be able to build experience in practical aspects of machine learning research, including research literature, aspects of implementation, and reproducibility challenges.
InhaltThe course will be structured as sections taught by different PostDocs specialized in the relevant fields. Each section will showcase an advanced research topic in machine learning, first introducing it and motivating it in the context of current technological or scientific advancement, then providing practical applications that students can experiment with, ideally with the aim of reproducing a very simple, known result in the specific field.
The tentative list of topics for this year is 3D scene understanding, graph neural networks, causal discovery, event-based sensors, trustworthy AI, reinforcement learning and visual text analytics. The last weeks of the course will be reserved for the implementation of the final project that the students can select among one of the presented areas.
Voraussetzungen / BesonderesParticipants should have basic knowledge about machine learning and statistics (e.g. Introduction to Machine Learning course or equivalent) and programming.


Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte4 KP
PrüfendeA. Ilic, M. El-Assady, F. Engelmann, T. Kontogianni, A. Marx, G. Ramponi, A. Sanyal, M. Sorbaro Sindaci
Formunbenotete Semesterleistung
RepetitionRepetition nur nach erneuter Belegung der Lerneinheit möglich.
Zusatzinformation zum PrüfungsmodusFinal group project


Es werden nur die öffentlichen Lernmaterialien aufgeführt.


Keine Informationen zu Gruppen vorhanden.


PlätzeMaximal 50
VorrangDie Belegung der Lerneinheit ist bis 28.02.2022 nur durch die primäre Zielgruppe möglich
Primäre ZielgruppeData Science MSc (261000)
Informatik MSc (263000)
Doktorat Informatik (264002)
WartelisteBis 18.03.2022
BelegungsendeBelegung nur bis 18.03.2022 möglich

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