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Machine Learning with R, part 2

  • Number of credits 3 credits
  • Level Bachelor's level
  • Study form Web-based (online)
  • Starting Spring Term 2025

About the course

If you are interested in data-driven methods for predicting or decision-making, then this course is for you. The course focuses on advanced non-linear machine learning models both for tabular data and image data. If you have already taken the course Machine Learning with R, part 1, this is the perfect opportunity to deepen your skills in the rapidly evolving field of machine learning. However, it can also be taken as a standalone course since basic ideas and concepts of machine learning are reviewed during the first parts of the course. Ultimately, you will acquire knowledge about machine learning and will be able to apply these skills to real-world problems.

Machine learning with R, part 2, is running at 50% study pace and is given in English.

 

Application and eligibility

Machine Learning with R, part 2, 3 credits

Visa tillfällen för föregående termin Spring Term 2025 Det finns inga senare terminer för kursen

Starts

20 February 2025

Ends

24 March 2025

Study location

Varied

Language

English

Type of studies

Daytime, 50%, Distance

Number of mandatory meetings

2

Number of other meetings

None

Required Knowledge

7,5 ECTS in Statistics incl. R, e.g., Machine Learning with R, part 1 (7.5 ECTS). Proficiency in English equivalent to Swedish upper secondary course English B/6

 

Entry requirements

Selection

Academic credits

Application code

UMU-27916

Application

The online application opens 16 September 2024 at 13:00 CET. Application deadline is 15 October 2024. How to apply

Application and tuition fees

As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.

Application fee

SEK 900

Tuition fee, first instalment

SEK 5,480

Total fee

SEK 5,480

Contact us

Please be aware that the University is a public authority and that what you write here can be included in an official document. Therefore, be careful if you are writing about sensitive or personal matters in this contact form. If you have such an enquiry, please call us instead. All data will be treated in accordance with the General Data Protection Regulation.

Contactpersons for the course are:
Study advisor, Department of Statistics, Umeå School of Business, Economics and Statistics