Berlin, Germany

Advanced AI & Open Science

when 20 July 2020 - 14 August 2020
language English
duration 4 weeks
credits 5 EC
fee EUR 1950

Due to the Covid-19 outbreak, this program has been cancelled for 2020. Please check our website for the new TU Berlin Summer University Online program.

In this course, the students will learn the basic theory in reinforcement learning and implement algorithms of many deep reinforcement learning models in Tensorflow and OpenAI gym environment.

Deep reinforcement learning is cutting-edge method in AI. It is a combination of deep learning and reinforcement learning, which has led to AlphaGo beating a world champion, which can play Atari games at a superhuman level, and which has been applied in self-driving cars.

We use the Python programming language for the entire course. While using various open source libraries for computing and data visualization, we will also introduce the students the best practices in open science and how to contribute to open source projects. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the tutorials and will team up to practice the newly learned skills in a real programming project — an entertaining computer game.

Course leader

Dr. Vaios Laschos
Dr. Rong Guo
M.Sc. Youssef Kashef

Target group

The target group includes current university students who have completed at least one year of their studies (Bachelor's, Master's or PhD level). Working professionals with equivalent work experience are also welcome to apply.
Basic programming skills (students should be able to write and run small programs in the language of their choice and know what software library and interface means) and basic knowledge in linear algebra and statistics/probability theory, e.g., gradient, probability distributions.

Course aim

In this course, the students will learn how to

● Apply a variety of advanced reinforcement learning algorithms to any problem

● Writing, Organizing, documenting, and distributing scientific code in Python

Credits info

5 EC
5 ECTS (European Credit Transfer System) for the academic course.

Fee info

EUR 1950: The fee covers public transportation for the duration of the course, excursions, course materials, and a cultural program.