Probabilistic Graphical Models

About This Course

Probabilistic Graphical Models are central to modern artificial intelligence and machine learning. This course equips students with the knowledge and tools to represent uncertain relationships between variables, perform efficient inference, and learn model structures from data. Through a mix of lectures, tutorials, and project-based work, students will gain hands-on experience in building and applying PGMs to real-world datasets and challenges.

Learning Objectives

• Acquire subject-specific theoretical and methodological knowledge in probabilistic modeling.
• Develop skills to analyze uncertainty using structured probabilistic frameworks.
• Apply PGMs to practical challenges through concrete project work.
• Strengthen teamwork, analytical thinking, and presentation skills.

Study Programs

This course is mandatory for the following study programs.

• M.Sc. Applied AI

This course is offered in odd quarters and can, therefore¹, be selected as an elective in the following study programs:

• M.Sc. Cybersecurity
• M.Sc. Advanced Digital Reality
• M.Sc. Digital Leadership
• MBA Digital Technologies
• MBA Digital Transformation

¹: Generally all mandatory modules of a study program can be selected as an elective in all study programs in which they are not offered as a mandatory module. However, there are several rules that apply. First, at least half of the selected electives have to be taken from your study program. Second, all electives are only available in either odd or even quarters. Therefore, not all electives are available in all programs (given that you want to finish the program within the regular time frame and do not want to take that elective in parallel to your impact project.)

Micro Degree

• This course is offered as a micro degree.
• German UDS Micro Degrees are compatible with the European MOOC Consortiums Common Micro Credentials Framework.
• Micro Degrees will be rewarded with an equivalent of 5 ECTS.
• Micro Degrees are offered to non-regular students and require a fee of €900.

Requirements

None

General Information

• Teaching Format: Experience
• Total Workload Master: 125h (40h/85h) / 5 ECTS
• Total Workload MBA: 100h (40h/60h) / 4 ECTS
• Total Workload Micro Degree: 125h (40h/85h) / Equivalent to 5 ECTS
• Module coordinator: Dr. Felix Weitkämper
• Examinations: Quizzes, presentation(s), essay(s)/paper(s), project report(s), written exam (tbd) - Details will be announced with course start.
• Offered: Odd quarters