Grüezi! 🖐️

Welcome to our GSERM course Deep Learning: Fundamentals and Applications, taught by Prof. Dr. Damian Borth. In this course, theoretical and practical hands-on coding lab sessions alternate to provide a better learning experience. 📚💻

The guided coding labs will be taught by Marco Schreyer. The Python programming, Machine Learning, and Deep Learning lab materials are available and accessible through this GitHub repository. 🐍🤖

Please use a laptop computer (not a tablet) to participate fully in the lab courses.

Viel Spass beim Programmieren! 🎉 (Happy Coding!)

• Lectures: Daily 09:15-12:30 CEST ⏰, at the SQUARE building, room Hilti 1, 11-1071 (1st floor).
• Labs 🧪: Daily 13:30-15:15 CEST, at the SQUARE building, room Hilti 1, 11-1071 (1st floor).
• Office Hours: Daily 16:00-17:00 CEST, please send us a corresponding invitation via mail 📬.
• Announcements: All course-related announcements 🔔 and questions will happen on Canvas 🎨.

Just like the timetable of the Swiss Federal Railways 🚞, the following table lists all lab sessions, including the launchers of the corresponding notebooks 📚 . Click on the corresponding launchers to start the notebooks in the respective cloud environment. We aim to upload each lab notebook the day before the lab respectively.

Date	Lab	Topic	Description	Binder Notebook	Gesis Notebook	Colab Notebook
< Mon, June 10th	Lab 00	Prerequisite	Test Notebook
< Mon, June 10th	Lab 01	Prerequisite	Python Basics
< Mon, June 10th	Lab 02	Prerequisite	Python Libraries
Mon, June 10th	Lab 03	Machine Learning	(Naive) Bayes Theorem	tba	tba	tba
Tue, June 11th	Lab 04	Deep Learning	Artificial Neural Networks (ANNs)	tba	tba	tba
Wed, June 12th	Lab 05	Deep Learning	Convolutional Neural Networks (CNNs)	tba	tba	tba
Wed, June 12th	Lab 06	Deep Learning	Autoencoder Neural Networks (AENs)	tba	tba	tba
Thu, June 13th	Lab 07	Deep Learning	Recurrent Neural Networks (RNNs)	tba	tba	tba
Thu, June 13th	Lab 08	Deep Learning	Attention Neural Networks	tba	tba	tba
Thu, June 14th	Lab 09	Deep Learning	Generative Adversarial Networks (GANs)	tba	tba	tba
< Fri, June 14th	-	Deep Learning	Assignment	tba	tba	tba

You can also board the train to the labs by launching all lab notebooks in either or .

Please don't hesitate to send us all your questions using the course mail address: