Events Calendar
Data Literacy: Introduction to Artificial Intelligence and Machine Learning
The lecture begins with a general introduction to the concepts of artificial intelligence (AI) and machine learning (ML) from a computer science perspective, followed by a brief historical overview. To provide a basic understanding of the technologies and methods, an overview of AI/ML developments and breakthroughs in recent years follows, including the technical basics explained in an intuitive and accessible manner: neural networks, transformers, and generative AI. The lecture concludes with a discussion of several critical aspects of AI – in particular, bias in AI systems, resource and energy consumption, and societal impacts – as well as a (non-exhaustive) overview of AI/ML research activities at KIT, primarily from a computer science perspective.
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Registration for students, doctoral candidates, and KIT employees
Registration is required to participate in the lecture series. KIT employees may also participate in the lecture series after registering.
Students and doctoral candidates can earn credit points through active, regular participation and by writing a report or essay.
Registration for guest students
Guest students are warmly welcome to attend the lecture series. To participate, you must 1) register for the lecture series and 2) register as a guest student.
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Please register for the lecture series here: Registration via SignMeUp (if necessary, please register first as an external user for the portal)
- Please register as a guest student at KIT by October 31 at the latest (including the semester fee) to receive a guest student certificate as proof of eligibility. To do so, please fill out the application for admission as a guest student.
More information for guest students can be found on the following FORUM page.
Registration for selected dates
Students, doctoral candidates, KIT employees, and registered guest students at KIT may also attend individual sessions of the lecture series, subject to availability.
In this case, please register for the relevant sessions by emailing dataliteracy ∂does-not-exist.forum kit edu.
Please review the participation requirements at https://www.forum.kit.edu/dali.php#rv.
Prof. Dr. Pascal Friederich, Head of the AiMat (Artificial Intelligence for Materials Sciences) Group
Institute of Nanotechnology & Department of Informatics, KIT
Studium Generale. Forum Wissenschaft und Gesellschaft (FORUM)
Karlsruher Institut für Technologie (KIT)
Karlsruhe
Tel: 0721/608-44384
Mail: dataliteracy ∂does-not-exist.forum kit edu
https://www.forum.kit.edu/dali.php
