Study Content

The Applied Artificial Intelligence program offers a scientifically founded curriculum of state-of-the-art methods and technologies of AI and Machine Learning, coordinated and defined by AI experts from both the University and the business world.  

Artificial Intelligence, Machine Learning, Deep Learning, Visual Analytics and Autonomous Systems represent the core competencies for the development of intelligent applications. Knowledge in programming with Python and Java, data management and mathematical skills are important basic competences for an AI expert. In addition, ethical and legal aspects of the use of intelligent systems are taught as part of the program. In electives, individual specializations such as Natural Language Processing can be chosen. 

During the course of studies, the acquired AI skills can be directly implemented in projects and competitions, be it in robotics, predictive maintenance, energy engineering, or trade. A special championship for such practical application is the RoboCup, where both teams of the University, Team Sweaty and Team Magma, hold vice world championship titles.

  • Introduction to Artificial Intelligence

    The first-semester lecture and corresponding exercises for the Introduction to Artificial Intelligence is taught by Prof. Dr. Klaus Dorer. The video gives an overview of the topics of the first semester, as well as topics covered during the further course of study.

  • Visual Analytics

    In Visual Analytics you learn about the principles of visualization, various types of visualization, and how you can use them to communicate content. In the accompanying practical, you work with real-world data. The lecture and the practical course are taught by Dr. Daniela Oelke. 

  • Machine Learning 1 und 2

    In the lectures Machine Learning 1 and 2 and the corresponding practical held by Dr. Oelke, you learn in detail about procedures, methods and approaches of Machine Learning, enabling you to perform a complete data analysis, from the preprocessing of the data to the evaluation of the results with machine-learning methods. With the know-how from Visual Analytics you can visualize the results and communicate your solutions. 

  • Autonome Systeme (4th semester)

    The Autonomous Systems lecture and lab are taught by Prof. Dr. Klaus Dorer. The video gives you an insight into the topics covered in Autonomous Systems. The knowledge and skills acquired in this course provide the basis for competitions like the RoboCup, where teams from around the globe compete in applying the latest AI methods. Both RoboCup teams from Hochschule Offenburg, Sweaty and Magma, are vice world champions.

  • Künstliche Intelligenz und Ethik (6th semester)

    This module, taught by Dr. Gernot Meier, covers basic ethical positions from European cultural and intellectual history as well as current discussions related to the field of AI. You will get to know important aspects and concepts of so-called digital ethics, learn to assess fundamental ethical concepts, and understand their significance in public discussions.

  • Computer Vision (6th semester)

    Prof. Dr. Stefan Hensel is an expert in the field of computer vision. In this lecture and accompanying lab you learn about feature-based methods of machine vision and how to use deep neural networks for machine vision. Computer Vision is part of many AI applications, such as autonomous driving, and generally in applications where object recognition is important, for example in automatic quality inspection.

The first-semester lecture and corresponding exercises for the Introduction to Artificial Intelligence is taught by Prof. Dr. Klaus Dorer. The video gives an overview of the topics of the first semester, as well as topics covered during the further course of study.

Team Magma - Laufen Lernen mit maschinellem Lernen

In competitions like the RoboCup, teams from around the globe compete in applying the latest AI methods. Both RoboCup teams from Hochschule Offenburg, Sweaty and Magma, are vice world Champions.