This offering is not in the current catalogue. The information is retained from an earlier publication. Check the provider's current offering.
Stockholm University
Introduction to Machine Learning
Machine learning and artificial intelligence has a strong influence on society today, both in practice and in people’s minds. Many organisations, both in the public sector and in business, are trying to take advantage of the new technology. In this course you will be introduced to basic principles in the field of ma…
- Higher education
- Information unavailable
- 29 March 2027
- Stockholm
- Information unavailable
- 50 %
Overview
Machine learning and artificial intelligence has a strong influence on society today, both in practice and in people’s minds. Many organisations, both in the public sector and in business, are trying to take advantage of the new technology. In this course you will be introduced to basic principles in the field of machine learning, good practice, as well as some important and easily accessible methods. In exercises you get to experiment with these methods and learn how to use them in practice.
Admission scores
Entry requirements
For course admission knowledge equivalent to the following is required: Mathematics I, 30 ECTS credits (MM2001), Programming Techniques for Mathematicians (DA2004) 7.5 ECTS credits.
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
- 2027-03-29
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.su.da4004.48006.20271
- Last checked
- 2026-09-23T10:39:10.072499+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.da4004.48006.20271
- Offering identity in the source
- e.uoh.su.da4004.48006.20271
- Education-form source code
- HS
- Education code in the source
- DA4004
- Change time according to the source
- 2026-08-18T13:09:37
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.