Introduction to Deep Learning

General Information

Summer Semester 2020.

SWS: 3, ECTS: 5.

Available for master students from: Computational Science and EngineeringInformationssystemtechnikElektrotechnik, Communications Technology (at the moment).

The course will be conducted in English.

The material of the course and all imporant infromation is available at .

Important: The course will take place electronically in the summer semester 2020. Please check on Moodle for instructions.


The aim of the course is to acquire basic knowledge on deep learning. This includes classical neural network models and recent architectures. Topics such as convolutional neural networks, optimisation, regularisation, generative models, sequential models will be covered among others. In the exercise, the participants will implement some of the standard models for classification or regression, transfer learning, generative models and acquire knowledge on machine learning applications.


Background on linear algebra, calculus, optimisation and programming will be helpful.

There will be two hours lecture every week and two hour exercise almost every second week.

The registration is performed through

For further questions on the course, the students may contact the lecturer.

Exam: End of July / Beggining of August 2020.

Repetition Exam: September 2020.

Lecture Schedule

Date Time Room Topic Comments
20.04.2020 12:00 Online Introduction


27.04.2020 12:00 Online Machine learning basics  

Exercise Schedule

Date Time Room Topic Comments
04.05.2019 14:00 Online   Online




Jun.-Prof. Dr. rer. nat. Vasileios Belagiannis 
Raum: 41.2.214
Telefon: +49 (0)731 50 27004
E-Mail | Homepage


Strohbeck Jan, M. Sc.
Raum: 41.2.216
Telefon: +49 (0)731 50 27026
E-Mail | Homepage

Schedule and Place

Lecture: Monday, 12:00 - 14:00 Uhr (Online)

Exercise: Monday (every second week), 14:00 - 16:00 Uhr (Online)