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Root number
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482207 |
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Semester
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HS2025 |
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Type of course
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Seminar |
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Allocation to subject
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Psychology |
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Type of exam
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Written exam |
| Title |
Data Science in Psychology |
| Description |
The course is particularly suited to master students in psychology with an interest in modern, computer-based methods in psychology. In the course an overview over data science methods will be provided and the relation between machine learning and classical statistics will be clarified. The course will cover both so-called "supervised methods" like support vector machines (SVMs) and deep neural networks (DNNs) as well as "unsupervised methods" like k-means clustering. In addition it covers the fundamental differences between "frequentist" and "Bayesian" statistics, and it will explain the use of Markov Chain Monte Carlo (MCMC) methods in Bayesian statistics. All methods and algorithms will be related to psychological theories and experiments. Some algorithms may be demonstrated using MATLAB; however, the course can be taken without any knowledge of MATLAB.
Professorship: Cognitive Psychology, Perception and Research Methods |
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ILIAS-Link (Learning resource for course)
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Registrations are transmitted from CTS to ILIAS (no admission in ILIAS possible).
ILIAS
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Link to another web site
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| Lecturers |
Prof. Dr.
Felix Alexander Wichmann, Institute of Psychology, Cognitive Psychology, Perception and Methodology
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ECTS
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5 |
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Recognition as optional course possible
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No |
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Grading
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1 to 6 |
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| Dates |
Friday 19/9/2025 08:30-12:00
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Friday 3/10/2025 08:30-12:00
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Friday 17/10/2025 08:30-12:00
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Friday 7/11/2025 08:30-12:00
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Friday 14/11/2025 08:30-12:00
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Friday 28/11/2025 08:30-12:00
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Friday 12/12/2025 08:30-12:00
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Rooms
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
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