Introduction to Deep Learning

General Information

Summer Semester 2020.

SWS: 3, ECTS: 5.

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

The course will be conducted in English.

The material of the course and all imporant infromation is available at https://moodle.uni-ulm.de/ .

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

Objectives

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.

Participation

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 https://campusonline.uni-ulm.de.

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

 

 

Lecturer

Exercise

Schedule and Place

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

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