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AI as a major Minor - AIM@LMU

Artificial Intelligence as a major Minor - AIM@LMU

The advances and rapid developments that we are currently experiencing in the fields of artificial intelligence (AI) and machine learning (ML) are not only accompanied by far-reaching changes in our society, industry, and the economy but are also starting to influence other areas of science, in which AI methods open up new research perspectives. A basic understanding of the concepts and methods of AI and their potential, risks, and limitations is therefore not only of fundamental importance for students of the computer sciences and related subjects but is also becoming increasingly important for students of completely different disciplines.

Taking this development into account, Prof. Dr. Hüllermeier and his colleagues have set themselves the goal of designing a broad, interdisciplinary training program for students at the Ludwig-Maximilians-Universität (LMU) in Munich. The Federal Ministry of Education and Research (BMBF) is funding the program "Artificial Intelligence as a major Minor" (AIM@LMU) at LMU

The aim of our initiative is to give students from a wide range of disciplines the opportunity to supplement their primary field of study with customized AI training in the form of a minor, import module, or by acquiring additional certificates. Such an education is attractive for students in several respects: From a job-related, practical point of view, the students acquire skills that qualify them in a special way for the job market. From the point of view of research-oriented and qualifying teaching, students are optimally prepared for a branch of research that will be beneficial to their main subject. 

The course offer is individually coordinated with the respective subjects, but will follow one of two models:

  • Minor model for subjects with a minor of 30 ECTS (e.g. mathematics and some natural sciences) or 60 ECTS (typical for humanities and many social sciences) in the bachelor's degree, and
  • Import model for subjects without an actual minor, which typically have larger blocks of elective modules.
The minor is currently being planned and is expected to start in WiSe 2023/2024. For questions and information about how to participate, please contact the program coordinator

topAI Minor (30 ECTS /60 ECTS)

The minor subject model for the 60 ECTS minor will offer two blocks of 30 ECTS each in the bachelor’s degree, a “Basics” block and an “Artificial Intelligence” block (see figure below). For the 30 ECTS minor subjects, basic knowledge of mathematics and computer science/programming will be assumed so that the first block can be omitted.

Model

The first block "Basics" is intended to convey the essential prerequisites in mathematics, computer science, and statistics and includes the following modules: 

  • Mathematics (Linear algebra and analysis, 6 ECTS, 3 SWS lectures + 2 SWS exercise course)
  • Introduction to inductive statistics for students of the minor (6 ECTS, 4 SWS lectures + 2 SWS exercise course)
  • Introduction to programming (6 ECTS, 3 SWS lecture + 2 SWS exercise course)
  • Programming practical training (6 ECTS, 4 SWS practical training)
  • Mandatory elective (6 ECTS): Database systems, human-machine interaction, algorithms and data structures, data mining algorithms, logic and discrete structures, human computation, economic and social statistics, and other courses on request.

The second block, “Artificial Intelligence,” includes the following the AI courses:

  • Introduction to artificial intelligence (for the natural/ social sciences) (6 ECTS, 3 SWS lectures + 1 SWS exercise course)
  • Introduction to machine learning (for the natural/social sciences) (6 ECTS, 3 SWS lectures + 1 SWS exercise course)
  • Artificial intelligence in science and society (lecture series, 6 ECTS)
  • Practical applications of artificial intelligence (12 ECTS)
Overview of the 30 ECTS and 60 ECTS minor:

topScheduled Courses

SoSe 2022

WiSe 2022/2023 (tentative)

  • Mathematics (Linear algebra and analysis, 6ECTS) - Link to the lecture in the LSF. Link to the exercise in the LSF.
  • Introduction to programming (6 ECTS) - Link to the lecture in the LSF. Link to the exercise in the LSF.
  • Introduction to machine learning (for the natural sciences) (6 ECTS) Link to the LSF. Link to the Website.

SoSe 2023 (tentative)

  • Introduction to inductive statistics for minor students (6 ECTS)
  • Introduction to artificial intelligence (for the natural sciences) (6 ECTS)
  • Introduction to machine learning (for the natural sciences) (6 ECTS)
  • Artificial intelligence in science and society (6 ECTS)
Note: Starting with the SoSe 2023, the course "Introduction to machine learning (for the natural sciences)" will be offered during the summer semester and the course for the social sciences during the winter semesters.

topImport Model

The Import model enables a specific design for the respective subject in which both detailed previous knowledge and general framework conditions of the course structure, including the distribution of the available ECTS points, can be addressed. 

Compatible Subjects

The minor AIM@LMU is being built to offer an interdisciplinary training program for all students at the Ludwig-Maximilians-Universität (LMU) in Munich. We are currently working on preparing the integration of the Minor and import modules with individual institutes. Stay tuned for more information. 

Language

The courses of the "Basics" block will be taught primarily in German, and the courses of the "Artificial Intelligence" block will be taught either in German or English. 

topParticipating Partners

Institute for Informatics

Prof. Dr. Eyke Hüllermeier, Project Coordinator, Artificial Intelligence

Prof. Dr. Sven Strickroth, Programming, Technology-Enhanced Learning

Dr. Iris Trautmann, Jane Matveyeva, Project Administration and Management

Institute for Statistics

Prof. Dr. Thomas Augustin, Mathematics and Statistics

Prof. Dr. Bernd Bischl, Machine Learning

Institute for Physics

Prod. Dr. Jochen Weller, AI in Physics

topContact

For questions, contact the project coordinator or project administration.

Funded by:

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