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227-0085-59L 2 Credits BSC D-ITET , D-INFK

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Hands-On Deep Learning

Lecturers & Examiners: Prof. Dr. Roger Wattenhofer

The course unit can only be taken once. Repeated enrollment in a later semester is not creditable.

VVZ CR 4.65

Last Updated: 2026-06-01 11:31:03

Abstract

This lab introduces deep learning through the PyTorch framework in a series of hands-on exercises, exploring topics in computer vision, natural language processing, audio processing, graph neural networks, and representation learning.

Objective

This P&S introduces deep learning through the PyTorch framework in a series of hands-on examples, exploring topics in computer vision, natural language processing, graph neural networks, and representation learning. With the objective to expose students to both common and cutting-edge neural architectures and to build intuition about their inner working by the means of examples. Students learn about various network structures as building blocks and use them to solve worked examples and course challenges. After attending this course, students will be familiar with multi-layer perceptrons, convolutional neural networks, recurrent neural networks, transformer encoders, graph convolutional/isomorphism/attention networks, and autoencoders.

Content

For information about the lab, please visit https://disco.ethz.ch/courses/hs25/hodl/

Resources

Lecture Notes

Python Notebooks will be distributed to students before every session.

Learning Materials (Links)

Main link
Website

General Information

Language: English
Levels: BSC
Frequency: Semesterly recurring

Examination

Type: ungraded semester performance

Registration & Places

Max Places: 200

Course Components

Type	Title	Time & Place	Hours
practical/laboratory course	Hands-On Deep Learning	Mon 12:15-16:00 (HG G 1)	32 h semesterly

Offered In

Informatik Bachelor
- Wahlfächer (Es können auch Lehrveranstaltungen aus dem Master-Studiengang in Informatik gewählt werden. Es liegt in der Verantwortung der Studierenden, sicherzustellen, dass sie die Voraussetzungen für diese Lehrveranstaltungen erfüllen.)
Elektrotechnik und Informationstechnologie Bachelor
- Praktika, Projekte, Seminare (Es müssen mindestens 15 KP aus der Kategorie "Praktika, Projekte, Seminare" erworben werden.)
  - Projekte & Seminare (offen für alle)