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Uppsala University
Project in Software Development in Image Analysis and Machine Learning
The course consists of group work on a project from outside academia or research, as well as a number of lectures on topics related to the development of software products. Examples of topics for such lectures are a framework for software development (for example, agile methods such as Scrum), project and time plann…
- Higher education
- Information unavailable
- 31 August 2026
- Uppsala
- Information unavailable
- 50 %
Overview
The course consists of group work on a project from outside academia or research, as well as a number of lectures on topics related to the development of software products. Examples of topics for such lectures are a framework for software development (for example, agile methods such as Scrum), project and time planning, IP and licensing issues, business plan and market analysis, quality systems, rules and regulations, oral and written presentation, and ethics. The lectures are intertwined with the introduction of the projects, problem analysis and planning. The scope of the projects is suitable for groups of approximately six students. After the introductory phase, the students complete the projects, and at the end of the course, this is presented to the course participants and external project owners. Ethical considerations are integrated into the projects, with the goal that you should develop the ability to participate constructively in dialogue on ethical issues and motivate your choices. At a project level, we can imagine multidisciplinary teams in collaboration with other programs, which in a suitable way combine skills.
Admission scores
Entry requirements
120 credits including 40 credits in mathematics and 60 credits in computer science, including Statistical Machine Learning, a second course in computer programming, Introduction to Image Analysis or Computer-Assisted Image Analysis I and Data Ethics and Law. Participation in Deep Learning and Advanced Deep Learning for Image Analysis, or participation in Deep Machine Learning for Image Analysis. Proficiency in English equivalent to the Swedish upper secondary course English 6.
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
- 2026-08-31
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.uu.1md036.11612.20262
- Last checked
- 2026-09-23T10:39:41.205927+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
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- Programme or course starts
- Programme or course ends
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Previous upper-secondary schools and programmes
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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.uu.1md036.11612.20262
- Offering identity in the source
- e.uoh.uu.1md036.11612.20262
- Education-form source code
- HS
- Education code in the source
- 1MD036
- Change time according to the source
- 2026-03-09T12:14:26
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.