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Advanced simulation and machine learning

Course
FYM345
Master’s level
7.5 credits (ECTS)
Study pace
50%
Time
Day
Location
Göteborg
Language
English
Duration
-
Part of semester
Quarter 3 to 4

About

The course covers a selection of machine learning algorithms and statistical methods for simulating physical systems. The course is based on a set of projects, which are accompanied by lectures, and hands-on computer exercises. During the course, the students will be exposed to advanced scientific research problems, with the aim to reproduce state-of-the-art scientific results.

The students will use e.g. the Python programming language and relevant open-source libraries, and will learn to develop and structure computer codes for carrying out scientific and statistical data analyses.

This course is open to

Exchange students at the Faculty of Science and exchange students on a university-wide agreement. Please contact your international coordinator at the University of Gothenburg if you need to know more.

Entry requirements

Bachelors degree in physics or equivalent. Recommended courses: Learning from data and Computational physicsor equivalent.

Applicants must prove their knowledge of English: English 6/English B from Swedish Upper Secondary School or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.

English proficiency

Incoming students should have an English level equivalent of B2 or higher as courses and materials, including presentations and exams, will be in English.

To assess your English level, you can use the self-assessment grid for reference: https://europa.eu/europass/en/common-european-framework-reference

Application

Do you want to apply for exchange studies at the University of Gothenburg?

Read more on the page Apply for exchange studies