This offering is not in the current catalogue. The information is retained from an earlier publication. Check the provider's current offering.
University of Gothenburg
Advanced topics in machine learning
- Theoretical and computationals aspects of machine learning. - Advanced deep learning (Deep Neural Network) models. - Sequential decision making paradigms such as active learning/online learning/reinforcement learning.
- Higher education
- Information unavailable
- 31 August 2026
- Information unavailable
- Information unavailable
- 50 %
Overview
- Theoretical and computationals aspects of machine learning. - Advanced deep learning (Deep Neural Network) models. - Sequential decision making paradigms such as active learning/online learning/reinforcement learning.
Admission scores
Entry requirements
To be eligible for the course the student must have successfully completed courses in: - 7\.5 credits of programming (Python experience desirable but not absolutely required) - 7\.5 credits of a data structures or basic algorithm course, or the course DIT374 - 7\.5 credits of basic probability and statistics - 7\.5 credits of calculus - 7\.5 credits of linear algebra - 7\.5 credits of a standard basic course in machine learning (for example DIT381, MSA220 or DIT866) Applicants must prove knowledge of English: English 6/English level 2 or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2026-08-31
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.gu.dit471.86012.20262
- Last checked
- 2026-09-23T10:36:42.164498+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
Programme content
Study structure
Application and important dates
- Programme or course starts
- Programme or course ends
Salary and salary distribution
Common occupations after graduation
Students
Geographical background
Previous upper-secondary schools and programmes
Completion and outcomes
About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.gu.dit471.86012.20262
- Offering identity in the source
- e.uoh.gu.dit471.86012.20262
- Education-form source code
- HS
- Education code in the source
- DIT471
- Change time according to the source
- 2026-02-17T15:42:05
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.