Introduction to Deep Learning (I2DL) (IN2346)

Introduction to Deep Learning (I2DL) (IN2346)

Welcome to the Introduction to Deep Learning course offered in SS20.

Update: COVID-19

The course will be held virtually. Links to streams and videos will be posted on moodle and on this website.


Mondays (14:00-16:00) - HOERSAAL MI HS 1 (00.02.001) (Virtually for now)

Lecturers: Prof. Dr. Laura Leal-Taixe and Prof. Dr. Matthias Niessner


SWS: 4


Thursdays (08:00-10:00) - Interims Hoersaal 1 (101) (Virtually for now)

Lead Teaching Assistants: Patrick Dendorfer and Andreas Rössler

Student Teaching Assistants: Felix Altenberger, Victor Armegioiu, Hanzhi Chen, Daoyi Gao, Pascal Herrmann, Felix Meissen, Andreea-Alexandra Musat, Chinmay Prabhakar, Yujiao Shentu, Sophia Wagner, Xinpeng Wang

For details about the exercises please refer to the first tutorial session. In particular, you will submit your solutions via our submission website.

Lecture Slides and Recordings

Tutorial Sessions


Office hours

In addition to the tutorial we also offer to discuss questions in person. This semester, the office hours will be held via TUM-Zoom. For each office hour, we provide a separate zoom-link, see announcement on Moodle. Please keep the following in mind to ensure the office hours remain helpful for everyone:

Office hours start on the 27th of April.

Final Exam



We use Moodle for discussions and to distribute important information. Please check the News and Discussion boards regularly or subscribe to them. The slides and all material will also be posted and maintained on Moodle.

External (non-TUM) Students

We want to provide access to our lecture for as many students as possible. If you are affiliated with TUM (e.g. LMU student, Ph.D. student, TUM student who cannot register for courses yet but have a TUM token, etc.), please register through this form , and we will add you to our moodle course.

If you are a student from another university or simply interested in Deep Learning, follow this link to the moodle course and sign in as a guest. As a guest, you have access to the lecture and exercise material, but you won't be able to submit exercises or take the exam.

Contact us

If you have any questions regarding the organization of the course, do not hesitate to contact us at:

For questions on the syllabus, exercises or any other questions on the content of the lecture, we will use the Moodle discussion board.


Future Semesters

This class will be offered next semester (WS20/21) as well.