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Mälardalen University
AI-driven Decision Support Systems for Energy and Production Operations
This course explores the integration of artificial intelligence (AI) in decision support systems specifically tailored for the energy and production sectors. You will learn how AI technologies, such as machine learning, optimization, and data analytics, are transforming traditional operational strategies, enhancing…
- Higher education
- Information unavailable
- 18 January 2027
- Ortsoberoende
- Information unavailable
- 25 %
Overview
This course explores the integration of artificial intelligence (AI) in decision support systems specifically tailored for the energy and production sectors. You will learn how AI technologies, such as machine learning, optimization, and data analytics, are transforming traditional operational strategies, enhancing decision-making processes, and driving efficiency in energy and production operations. The course covers foundational concepts of AI and decision support systems, along with practical applications such as predictive maintenance, demand forecasting, process optimization, and real-time decision support. Through hands-on projects, case studies, and industry-relevant examples, you will gain insight into designing and implementing AI-driven solutions that improve operational performance, reduce costs, and support sustainability goals. By the end of the course, you will be equipped with the skills to develop and apply AI-driven decision support systems to solve complex challenges in energy and production environments. This course is ideal for professionals and students interested in leveraging AI for operational excellence in the energy and production industries.
Admission scores
Entry requirements
90 credits in engineering/technology, or 30 credits in engineering/technology and at least 2 years' experience in full-time employment in a relevant area within industry, or at least 3 years' experience in full-time employment in a relevant area within industry. In addition, English course 6 or English level 2 are required.
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
- 2027-01-18
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.mdu.era323.20597.20271
- Last checked
- 2026-09-23T10:38:46.21657+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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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.mdu.era323.20597.20271
- Offering identity in the source
- e.uoh.mdu.era323.20597.20271
- Education-form source code
- HS
- Education code in the source
- ERA323
- Change time according to the source
- 2026-09-09T15:38:18
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.