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Machine Learning with R, part 2

  • Number of credits 3 credits
  • Level Bachelor's level
  • Starting Spring Term 2024

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

Det finns inga tidigare terminer för kursen Spring Term 2024 Visa tillfällen för efterkommande termin

The information below is only for exchange students

Starts

15 February 2024

Ends

19 March 2024

Study location

Umeå

Language

English

Type of studies

Daytime, 50%

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

 

Selection

Students applying for courses within a double degree exchange agreement, within the departments own agreements will be given first priority. Then will - in turn - candidates within the departments own agreements, faculty agreements, central exchange agreements and other departmental agreements be selected.

Application code

UMU-A2789

Application

This application round is only intended for nominated exchange students. Information about deadlines can be found in the e-mail instruction that nominated students receive. The application period is closed.

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