Module PY4220-KP06

Duration

1 Semester

Turnus of offer

each winter semester

Credit points

6

Course of studies, specific fields and terms:

• Master Psychology - Cognitive Systems 2027, compulsory, psychology
• Master Psychology - Cognitive Systems 2022, compulsory, psychology

Classes and lectures:

• PY4240-KP06-S: Computational Psychology (seminar, 2 SWS)
• PY4240-KP06-V: Computational Psychology (lecture, 2 SWS)

Workload:

• 60 hours in-classroom work
• 120 hours private studies

Contents of teaching:

• Understanding computer-based models in psychology
• Apply Bayesian models and predictive coding
• Theories and models for decision-making
• Researching computer-aided psychiatry and mental disorders
• Use of machine learning and big data in psychology
• Critical evaluation of explanation and prediction in psychological research

Qualification-goals/Competencies:

• Students have a basic understanding of computational models and their role in explaining cognitive and neural processes.
• You have skills in applying Bayesian models and predictive coding to explain perception, cognition, and psychiatric disorders.
• You understand how computational models contribute to understanding, diagnosing, and potentially treating psychiatric disorders such as schizophrenia, depression, and addiction.
• You can apply machine learning techniques and large-scale data analysis to cognitive psychology and behavioral prediction.
• Understanding explanatory versus predictive modeling in psychology

Grading through:

• written exam

Responsible for this module:

• Prof. Dr. rer. nat. Jonas Obleser

Teacher:

• Department of Psychology
• Prof. Dr. rer. nat. Jonas Obleser
• Dr. Niels Kloosterman

Language:

• German and English skills required

Notes:

Last Updated:

13.11.2025