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Linköping University
Statistics and Machine Learning, Master's Programme - Second admission round (open only for Swedish/EU students)
Unleash the power of data and statistics to make the right decisions happen. The rapid development of information technologies has overwhelmed society with enormous volumes of information generated by large or complex systems from telecommunications, robotics, medicine, business and many other fields. This master’…
- Higher education
- Information unavailable
- 24 August 2026
- Information unavailable
- Information unavailable
- 100 %
Overview
Unleash the power of data and statistics to make the right decisions happen. The rapid development of information technologies has overwhelmed society with enormous volumes of information generated by large or complex systems from telecommunications, robotics, medicine, business and many other fields. This master’s programme meets the challenges of learning from these complex volumes by means of models and algorithms from machine learning, data mining and other computer-intensive statistical methods. By joining us, you will increase the efficiency and productivity of the systems and make them smarter and more autonomous. We integrate statistical modelling and analysis with machine learning, data mining and data management to give you unique skills. The programme focusses on modern methods from machine learning and database management that use the power of statistics to build efficient models and make reliable predictions and optimal decisions. You will gain deep theoretical knowledge as well as practical experience from extensive amounts of laboratory work. Depending on your interests, you will work towards your thesis at a company, a governmental institution or a research unit at LiU. There you can apply your knowledge to a real problem and meet people who use advanced data analytics in practice or you can go deeper into the research. There is a rapidly increasing demand for specialists who are able to exploit the new wealth of information in large and complex systems. Business, telecommunications, IT and medicine are just a few examples of areas where you will be wanted for advanced analytical positions. You will also be well prepared for an academic career, should you choose to continue into research and pursue PhD studies.
Admission scores
Entry requirements
Bachelor's degree equivalent to a Swedish Kandidatexamen in one of the following subject areas: -statistics -mathematics -applied mathematics -computer science -engineering or a similar degree Completed courses with passing grade in following subjects: - calculus - linear algebra - statistics - programming English corresponding to the level of English in Swedish upper secondary education (Engelska 6 or Engelska nivå 2) Exemption from Swedish
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
- 2026-08-24
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.liu.f7mml.90006.20262
- Last checked
- 2026-09-23T10:38:02.783888+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.liu.f7mml.90006.20262
- Offering identity in the source
- e.uoh.liu.f7mml.90006.20262
- Education-form source code
- HS
- Education code in the source
- F7MML
- Change time according to the source
- 2025-11-14T09:26:15
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.