Physics: Research in Physics, Classical/Quantum Information
| Course | EC | Semester 1 | Semester 2 |
|---|---|---|---|
Physics programme (60 EC) |
|||
|
Mandatory courses (30EC) |
|||
| Introduction to Machine Learning | 6 | ||
| Quantum Information | 3 | ||
| Statistical Physics a | 6 | ||
| Academic and Professional Skills (Science) | 3 | ||
| Computational Physics (6 EC) | 6 | ||
| Physics and Classical / Quantum Information | 6 | ||
|
Choice of 2 courses from the list of core courses presented below |
|||
| Introduction to Deep Learning | 6 | ||
| Statistical learning - old curriculum | 6 | ||
| Seminar Advances in Deep Learning | 6 | ||
| Applied Quantum Algorithms | 6 | ||
| Foundations of Statistics and Machine Learning | 6 | ||
| Reinforcement Learning | 6 | ||
|
Electives ≥18EC (from either the list of core courses or the list of courses below, and max. 6EC from MSc programmes outside Physics) |
|||
| Automated Machine Learning | 6 | ||
| Complex Networks (BM) | 6 | ||
| Econophysics | 6 | ||
| Quantum Theory | 6 | ||
| Statistical Physics b | 3 | ||
Research Project in Physics with Data ScienceAll research projects are performed under the responsibility of a LION staff member. The main research project can be extended to 42 EC (research=36 EC, thesis=4 EC, presentation=2 EC) and combined with a smaller 18 EC project or internship, with the approval of the Study Advisor and the Board of Examiners. |
|||
|
Research project (36EC) |
|||
| Research (30 EC) | 30 | ||
| Thesis (4 EC) | 4 | ||
| Presentation (2 EC) | 2 | ||
|
Second small research project or internship (24 EC) |
|||
| Research (20 EC) | 20 | ||
| Thesis (3 EC) | 3 | ||
| Presentation (1 EC) | 1 | ||