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227-0085-59L 2 Credits BSC D-ITET
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P&S: Hands-On Deep Learning

Lecturers & Examiners: Prof. Dr. Roger Wattenhofer
Course can only be registered for once. A repeatedly registration in a later semester is not chargeable.
VVZ CR 4.65

Last Updated: 2026-02-05 16:14:43

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

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.

Resources

Lecture Notes

Python Notebooks will be distributed to students before every session.

Learning Materials (Links)

General Information

Language
English
Levels
BSC
Frequency
Semesterly recurring

Examination

Type
ungraded semester performance

Registration & Places

Limited places (Special selection)
Signup Start
15.09.2023
Signup End
29.09.2023
Priority: Registration for the course unit is only possible for the primary target group

Course Components

Type Title Time & Place Hours
practical/laboratory course P&S: Hands-On Deep Learning
Für den Zugang zum Angebot und zur Einschreibung loggen Sie sich hier ein (mit Ihrem n.ETHZ account): Bitte beachten Sie, dass die Seite jeweils erst zwei Wochen vor Semesterbeginn zugänglich ist und im Verlauf des Semesters wieder abgeschaltet wird. Die Einschreibung ist nur von Freitag vor Semesterbeginn bis zum ersten Freitagmittag im Semester möglich. To access the offer and to enroll for courses log in (with your n.ethz account): Please note that the P&S-site is accessible no earlier than two weeks before the start of the semester until four weeks after the start of the semester. Enrollment is only possible from Friday before the start of the semester until noon of the first Friday in the semester.
  • Tue 08:15-12:00 (ETZ D 61.1)
  • Tue 08:15-12:00 (ETZ D 96.1)
32 h semesterly

Offered In