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Jönköping University
Machine Learning and AI in Manufacturing Analytics
**Transform manufacturing performance with the power of AI and machine learning.**<br> *Machine Learning and AI in Manufacturing Analytics* equips professionals with the tools and knowledge to harness predictive modeling, anomaly detection, and explainable AI to improve quality, reduce waste, and optimize industrial…
- Higher education
- Information unavailable
- 9 November 2026
- Jönköping
- Information unavailable
- 25 %
Overview
**Transform manufacturing performance with the power of AI and machine learning.**<br> *Machine Learning and AI in Manufacturing Analytics* equips professionals with the tools and knowledge to harness predictive modeling, anomaly detection, and explainable AI to improve quality, reduce waste, and optimize industrial processes. Through hands-on experience with real manufacturing data, participants gain practical expertise in modern machine learning techniques, robust validation methods, and responsible AI practices including transparency, fairness, and risk management. This course emphasizes the deployment of interpretable, sustainable, and trustworthy AI solutions that enhance decision-making and support the transition toward more efficient, resilient, and data-driven manufacturing system.
Admission scores
Entry requirements
Academic degree of at least 180 ECTS credits within Engineering and/or Technology or passed courses of at least 40 credits in the main field of study within Engineering and/or Technology and at least 1 year of work experience in the manufacturing industry or at least 4 years of work experience in the manufacturing industry. Proof of English proficiency is 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
- 2026-11-09
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.hj.t2moaf.13187.20262
- Last checked
- 2026-09-23T10:37:43.911976+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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- Programme or course ends
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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.hj.t2moaf.13187.20262
- Offering identity in the source
- e.uoh.hj.t2moaf.13187.20262
- Education-form source code
- HS
- Education code in the source
- T2MOAF
- Change time according to the source
- 2026-05-19T15:29:32
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.