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Root number
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482207 |
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Semester
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FS2023 |
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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 3/3/2023 08:30-12:15
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Friday 17/3/2023 08:30-12:15
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Friday 31/3/2023 08:30-12:15
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Friday 21/4/2023 08:30-12:15
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Friday 5/5/2023 08:30-12:15
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Friday 19/5/2023 08:30-12:15
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Friday 2/6/2023 08:30-12:15
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| Rooms |
Seminarraum B 005, Institutsgebäude vonRoll
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Seminarraum 005, Seminargebäude vonRoll
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
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