Welcome to the teaching and learning platform on machine learning and artificial intelligence!

The InterKI curriculum is a comprehensive, thematically broad range of courses and learning materials that you can use flexibly and tailored to your individual prior knowledge and interests. It is structured into four modules (" Basics", "Applications", "Advanced Courses", "AI in the societal context"), each of which branches out further into sub-modules. The program is aimed at students, PhD students, scientists and lecturers.

The courses offered in the current semester can be found below the short descriptions of the four modules.

The extensive, curated  Jupyter notebooks library hosts didactically edited examples from a wide range of difficulty levels and application areas.

 

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BASICS

The core element of the module Basics is the interdisciplinary lecture "Introduction to Machine Learning". In addition, you will find accompanying hands-on courses (hackatons) as well as a variety of self-study materials to supplement your ML and data science skills individually.
No programming experience and your skills in mathematics are already a bit rusty? - No problem at all! We offer preparatory materials and support for the introduction to programming and the installation of the necessary software as well as a compendium of the mathematical ML fundamentals.

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ADVANCED COURSES

If you have completed the introductory courses or have otherwise already mastered the basics of ML, you can jump right into the module Conceptual Deepenings. Here, you have the opportunity to specifically deepen your knowledge by learning about current and sophisticated AI architectures and learning strategies, or to delve deeper into the theoretical foundations of AI.  In addition, you can expand your understanding of AI by approaching the topic from other viewpoints, such as Bayesian statistics.


 

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AI IN THE SOCIETAL CONTEXT

It is no longer possible to imagine our everyday lives without AI.  The ethical and societal issues raised by the increasing use of AI have now also entered the political discourse. In the module AI in the Societal Context, we offer courses that focus on ethical and philosophical aspects of AI as well as on the topic of sustainability. In addition, you will find courses addressing the integration of AI into teacher training. If you are interested in starting a business from science, the submodule "AI and Start-ups" is perfect for you.

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COMPLEX APPLICATIONS

ML and AI have become an integral piece of the scientific methodological toolbox. In the module Complex Applications you will find courses on applications of ML and AI methods in the context of various current research fields: complex dynamical systems (physics), the theoretical analysis of molecular systems (chemistry/physics), molecular applications (chemistry), medicine, in particular medical imaging, and the analysis of human movements (sports sciences).