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Örebro University
Machine Learning
Machine learning is a subfield of artificial intelligence within computer science and includes techniques that enable machines (robots or software) to learn how to perform specific tasks based on data, rather than through explicit programming. Applications include image classification, predictive maintenance, text a…
- Higher education
- Information unavailable
- 18 January 2027
- Örebro
- Information unavailable
- 50 %
Overview
Machine learning is a subfield of artificial intelligence within computer science and includes techniques that enable machines (robots or software) to learn how to perform specific tasks based on data, rather than through explicit programming. Applications include image classification, predictive maintenance, text analysis, speech recognition, and the generation of images and text. This course provides an introduction to machine learning with the aim of developing an understanding of fundamental concepts, methods, and algorithms. This is achieved through hands-on work in which algorithms are implemented and modified almost from scratch, as well as through the study of data analysis, data preprocessing, model evaluation, identification of potential issues and misleading results, and practical recommendations for applying machine learning techniques. The course also includes a literature study that provides insight into current research, as well as a practical classification task and a final project that offer practical experience and skills for further studies in academia or professional work in industry with machine learning.
Admission scores
Entry requirements
Object-Oriented Programming, 7.5 Credits from Programming, 15 credits, and Algebra and Calculus for Students in Engineering, 15 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
- 2027-01-18
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.oru.dt150g.v5320.20271
- 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.
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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.oru.dt150g.v5320.20271
- Offering identity in the source
- e.uoh.oru.dt150g.v5320.20271
- Education-form source code
- HS
- Education code in the source
- DT150G
- Change time according to the source
- 2026-09-08T10:45:03
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.