Probabilistic Graphical Models
MICRO-DEGREEThis course introduces probabilistic graphical models, such as Bayesian networks and Markov random fields, focusing on their application in data analysis, machine learning, and decision-making.
Univ.-Prof. Dr. Felix Weitkämper
Head of Research Group "Statistical and Symbolic Artificial Intelligence"
Professor
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About
Felix Weitkämper is professor at the German University of Digital Science, contributing to the research and education on statistical and symbolic approaches to artificial intelligence. He studied Mathematics with Philosophy at the LMU in Munich and earned his DPhil in Mathematics (Logic) at the University of Oxford. Having spent a year with the educational charity Researchers in Schools in a vocational setting in the North of England, Felix Weitkämper joined the programming languages and AI group at the LMU as a postdoctoral researcher in 2020. He moved to the German University of Digital Science as a senior researcher in October 2024, before taking up his current position in April 2025. Felix Weitkämper's research focuses on interpretable, human-centered AI, combining statistical learning with logical reasoning.
Coordinated Study Programs
Machine Learning and Analytics
MICRO-DEGREEThis course covers how big data and machine learning support decision-making, focusing on methods like regression, neural networks, and SVMs, along with data pipelines and AI strategies.
Logic and Symbolic AI
MICRO-DEGREEThis module is an introduction to logic and symbolic AI. We introduce the principles of computational logic and the fundamentals of the logic programming paradigm as exemplified by the Prolog language.
Coordinated Study Modules
Envision & Strategize: Big Data, Software Systems, Cloud Computing (MSc)
Workload: 125 hours
Quick Info
Position:
Professor
Role:
Head of Research Group "Statistical and Symbolic Artificial Intelligence"
Teaching Subject:
Statistical and Symbolic Artificial Intelligence
Research Centers
Speaker