270095 UE Machine learning for molecules and materials (2022W)
2.00 ECTS (2.00 SWS), SPL 27 - Chemie
Continuous assessment of course work
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Sa 10.09.2022 08:00 to We 28.09.2022 23:59
- Deregistration possible until We 28.09.2022 23:59
max. 24 participants
Lecture and exercises will take place on Mondays from 9:30 to 12:30 in the PC pool, Währinger Str. 17, 2nd floor.
Aims, contents and method of the course
Assessment and permitted materials
Performance will be assessed through participation in the computer exercises. There is the possibility to prove the performance by solving an own problem from chemistry by means of machine learning.
Minimum requirements and assessment criteria
Basic knowledge of theoretical chemistry (bachelor level: Hartree-Fock, harmonic oscillator, basic mathematics, etc.) is assumed. The grade is composed of the averaged results of the various computer exercises and the participation in the exercises.
Content of the course.
- C. Bishop, Pattern recognition and machine Learning
Association in the course directory
CH-MAT-01, TC-3, PC-4, WD3, D.4, Design
Last modified: Mo 13.03.2023 10:09
- Understanding and overview of machine learning methods for molecules and materials.
- Ability to write small programs in Python, with an emphasis on machine learning for theoretical chemistry.
- Knowledge of solving problems with machine learning.