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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

Uppgift saknasVerified data is not connected to this education offering.

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.

Programme content

Uppgift saknasVerified data is not connected to this education offering.

Study structure

Uppgift saknasVerified data is not connected to this education offering.

Application and important dates

  1. Programme or course starts
  2. Programme or course ends

Salary and salary distribution

Uppgift saknasVerified data is not connected to this education offering.

Common occupations after graduation

Uppgift saknasVerified data is not connected to this education offering.

Students

Uppgift saknasVerified data is not connected to this education offering.

Geographical background

Uppgift saknasVerified data is not connected to this education offering.

Previous upper-secondary schools and programmes

Uppgift saknasVerified data is not connected to this education offering.

Completion and outcomes

Uppgift saknasVerified data is not connected to this education offering.

About the provider

Örebro University

Provider for the published education offering.

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.