This offering is not in the current catalogue. The information is retained from an earlier publication. Check the provider's current offering.
Mid Sweden University
Electrical Engineering MA, Applied Machine Learning
AI and machine Learning are gaining ground in industry and government, and knowledge of how to apply machine learning is becoming increasingly important. The purpose of the course is to provide an introduction to several subfields within machine learning and to orientate about basic methods and algorithms available…
- Higher education
- Information unavailable
- 22 March 2027
- Information unavailable
- Information unavailable
- 50 %
Overview
AI and machine Learning are gaining ground in industry and government, and knowledge of how to apply machine learning is becoming increasingly important. The purpose of the course is to provide an introduction to several subfields within machine learning and to orientate about basic methods and algorithms available in these fields. To convey breadth and depth in machine learning and its application in measurement technology.
Admission scores
Entry requirements
Degree of Bachelor of Science, Degree of Bachelor of Science Engineering (at least 180 credits), or equivalent, with at least 60 credits in Electrical Engineering or Computer Science.
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
- 2027-03-22
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.miu.et003a.d2x60.20271
- Last checked
- 2026-09-23T10:38:51.696898+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.miu.et003a.d2x60.20271
- Offering identity in the source
- e.uoh.miu.et003a.d2x60.20271
- Education-form source code
- HS
- Education code in the source
- ET003A
- Change time according to the source
- 2026-01-07T15:16:54
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.