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Root number
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478977 |
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Semester
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HS2024 |
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Type of course
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Lecture |
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Allocation to subject
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Artificial Intelligence in Medicine |
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Type of exam
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Written exam |
| Title |
Reinforcement Learning |
| Description |
Teaching assistant(s):
- Maria Panagiotou
- Ethan Dack
- Lubnaa Abdur Rahman
Module:
Artificial Intelligence
Prerequisites:
- Linear algebra, Probability, AI, ML
- Python
Required material or equipment:
- Laptop or other computer system with Python installed
Textbook(s):
- Richard S. Sutton, Andrew G. Barto, Reinforcement Learning. An Introduction, The MIT Press, 2020.
- DeepMind Learning Resources (Hado van Hasselt, Diana Borsa & Matteo Hessel), Reinforcement Learning Lecture Series 2021.
Course policies and classroom rules of conduct:
- Academic dishonesty, plagiarism, and any other kind of fraud will lead to the exclusion from the course.
- Attendance required
- Punctuality
- Homework and project must be handed on time |
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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 |
Dr.
Lorenzo Brigato, ARTORG Center for Biomedical Engineering Research ✉
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Prof. Dr.
Stavroula Mougiakakou, ARTORG Center - Artificial Intelligence in Health and Nutrition ✉
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Ioannis Papathanail, ARTORG Center for Biomedical Engineering Research ✉
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ECTS
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5 |
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Recognition as optional course possible
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Yes |
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Grading
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1 to 6 |
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| Dates |
Thursday 12:15-14:00 Weekly
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Thursday 23/1/2025 12:15-14:00
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| Rooms |
Hörraum 106, Hauptgebäude H4
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Seminarraum 206, Hauptgebäude H4
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| External rooms |
106, Hauptgebäude H4
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
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