This offering is not in the current catalogue. The information is retained from an earlier publication. Check the provider's current offering.
Stockholm University
Machine learning
Machine Learning is methodologically based on statistical theory, but instead of fociusing on inference about unknown population- and model parameters based on sampling, machine learning aims to find general patterns, mainly to make predictions. Among the areas of applications for machine learning, are marketing, fi…
- Higher education
- Information unavailable
- 31 August 2026
- Information unavailable
- Information unavailable
- 50 %
Overview
Machine Learning is methodologically based on statistical theory, but instead of fociusing on inference about unknown population- and model parameters based on sampling, machine learning aims to find general patterns, mainly to make predictions. Among the areas of applications for machine learning, are marketing, finance, economics, and textual analysis within digital humanities and social scienses.
Admission scores
Entry requirements
90 ECTS credits first-cycle (basic level) courses, of which 60 ECTS credits in Statistics and 15 ECTS credits bachelor’s thesis in Statistics or other subject with quantitative focus, and Statistical Theory with Applications, first-cycle, 15 ECTS or equivalent. R programming, second-cycle (advanced level), 7.5 ECTS or equivalent. English 6 or equivalent.
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.su.st5401.39009.20262
- Last checked
- 2026-09-23T10:39:22.250813+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.su.st5401.39009.20262
- Offering identity in the source
- e.uoh.su.st5401.39009.20262
- Education-form source code
- HS
- Education code in the source
- ST5401
- Change time according to the source
- 2025-10-03T13:52:44
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.