| Automated Scientific Discovery |
| DozentIn:Sebastian Musslick |
| Veranstaltungstyp:Vorlesung und Seminar (Offizielle Lehrveranstaltungen) |
| Ort:35/E16: Montag, 04.08.2025 - Donnerstag, 07.08.2025, Montag, 11.08.2025 - Mittwoch, 13.08.2025 09:00 - 17:00, Dienstag, 26.08.2025 10:30 - 17:00,
35/E23-E24: Freitag, 08.08.2025 09:00 - 17:00,
69/E23: Donnerstag, 09.10.2025 12:00 - 16:00 |
| Semester:SoSe 2025 |
Zeiten:Termine am Montag, 04.08.2025 - Freitag, 08.08.2025, Montag, 11.08.2025 - Mittwoch, 13.08.2025 09:00 - 17:00, Dienstag, 26.08.2025 10:30 - 17:00, Donnerstag, 09.10.2025 12:00 - 16:00, Ort: 35/E16, 35/E23-E24, 69/E23
Erster Termin:Montag, 04.08.2025 09:00 - 17:00, Ort: 35/E16 |
Beschreibung:Course Description:
In this block course offers an introduction to cutting-edge methods in automated scientific discovery and AI for science, with a focus on applications in the cognitive science. Through a combination of interactive lectures and hands-on programming exercises, students will explore how automation techniques and AI can be used to accelerate research in psychology and neuroscience. Topics include automated experimental design, model discovery, and the use of AI scientists to uncover the computational principles underlying human cognition.
Learning Objectives:
By the end of this course, students will:
1. Be familiar with professional open-source software development practices on GitHub (code review, unit tests, CI/CD)
2. Understand opportunities and challenges of automating scientific practice for the study of mind and brain (i.e., learn what it takes to build an AI scientist for the study of human cognition)
3. Be able to automate the generation of experimental designs
4. Be able to automate the generation of web-based behavioral experiments
5. Be able to automate behavioral data collection
6. Be able to use and evaluate algorithms for automated scientific model discovery
Prerequisites:
Prospective students should have completed the course “Modeling in Cognitive Science” and possess a working knowledge of the Python programming language.
Course Format:
Delivery Method: On-site
Type of Contact & Contact Hours: The block course will likely occur August 4-15; exact times are TBD
Selection Process: The course is limited to 20 participants. In case of higher demand, participants will be selected based on a lottery.
Assessment and Grading:
- Student participate in three group-based hackathon challenges involving the development python notebooks. Each the three hackathon challenges will make up 1/3 of the final grase.
Important Dates:
N/A
Required Texts and Materials or Further Resources:
- All required materials will be provided via this Stud.IP course
Will this class be offered again in the future?
- Yes, every summer term |
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