## Physics: Research in Physics, Classical/Quantum Information

Vak | EC | Semester 1 | Semester 2 |
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## Physics programme (60 EC) |
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Mandatory courses (30EC) |
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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 |
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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) |
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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. |
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Research project (36EC) |
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Research (30 EC) | 30 | ||

Thesis (4 EC) | 4 | ||

Presentation (2 EC) | 2 | ||

Second small research project or internship (24 EC) |
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Research (20 EC) | 20 | ||

Thesis (3 EC) | 3 | ||

Presentation (1 EC) | 1 |