Fundamentals and Methods of Artificial Intelligence (Module)

The continuing education module "Fundamentals and Methods of Artificial Intelligence" is designed for working professionals who wish to balance their careers with their studies.

Faculty

Electrical Engineering

Degree

Certificate

Study formats

Working Students, Continuing Education

Language

German

Study start

Winter Term

Standard Duration

1 Semester

Admission

Admission Type below

This continuing education module covers the methodological, theoretical, and technological fundamentals of industrial artificial intelligence. It lays the groundwork for the development and evaluation of modern AI solutions in an industrial setting. Participants gain a structured overview of the concepts, architectures, and application areas of intelligent, learning, and autonomous systems. 

Through practical industry examples and by working on their own problems (“solve your own problem”), participants can immediately experience and apply the material covered. Participants gain an understanding of the fundamental different areas of industrial artificial intelligence, how they work, their areas of application, and their practical limitations.

Continuing Education Module with Career Prospects

This continuing education module will also be part of the Industrial AI - Foundation Level certificate program (30 ECTS credits), which is currently being developed. Upon successful completion of the module, you will earn 5 ECTS credits, which can be applied toward the certificate program should you decide to enroll in it at a later date.

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Module Content

  • Introduction to Industrial Artificial Intelligence: Development, Terminology, Subfields of AI, and Architectures
  • Subsymbolic AI: Machine Learning Methods, Deep Learning, Transformers (especially on-premise and edge AI)
  • Symbolic AI: in particular, knowledge-based systems, knowledge graphs, ontologies, and logical reasoning
  • Hybrid AI: Combination of data-driven and knowledge-based methods
  • Performance metrics for industrial AI systems, e.g., trustworthiness, transparency, auditability, and explainability

Target Audience

Professionals who want to better understand and help shape industrial processes, data, and technological development opportunities:

  • technical specialists and managers in production, development, design, automation, quality assurance, or maintenance,
  • technicians with relevant practical experience
  • Individuals in project or transformation roles

No prior knowledge of artificial intelligence is required. The course content is suitable for both beginners and those who wish to systematically build their knowledge and expand their expertise in industrial applications and implementation.

Dates

On-site dates (Augsburg University of Technology):

  • Friday, October 16, 2026, 9:00 a.m. – 5:00 p.m., followed by a get-together
    Introduction and Fundamentals (Prof. Dr. Legat),
    Knowledge-Based Systems (A. Müller)

     
  • Saturday, October 17, 2026, 9:00 a
    .m. – 4:30 p.m. Data-Based Systems & Edge AI (Prof. Dr. Dietrich)

     
  • Saturday, December 5, 2026, 9:00 a.m. – 5:00 p.m.
    Results workshop on participants’ own use cases for “Edge AI” and “knowledge-based systems”
    (Prof. Dr. Dietrich, A. Müller),
    Wrap-up Workshop and Certificate Ceremony (Prof. Dr. Legat)

In addition to the in-person sessions, six one-on-one online consultation hours will be offered by appointment. During these sessions, participants’ projects can be discussed, technical questions clarified, and individual challenges addressed collaboratively.

Faculty

Prof. Dr. Christoph Legat is a professor at THA, where his teaching and research focus on the combination of digital modeling and industrial artificial intelligence in regulated application areas.

Prof. Dr. Simon Dietrich is a professor of applied robotics at THA. His work focuses on intelligent automation systems utilizing machine learning and cognitive robotics.

Andreas W. Müller is an expert in knowledge engineering at Schaeffler Technologies AG. His work focuses on the development and implementation of explainable and trustworthy industrial AI systems.

Registration

Registration is done through eveeno.

Registration Fee

The participation fee is 2,590 euros.

Participation is subject to our General Terms and Conditions, which you can find on our website at www.tha.de/ibi.

The fee includes participation in the modules, refreshments during breaks, and refreshments at the get-together.

Organization:
industrial.ai@THA
Tel. 0821 5586-4000

Contact Person