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Course schedule

Preliminary timeplan

  • Ca 15 August, kick off (1 h on zoom) for P0. Time decided together with participants.
  • 28 september: hand-in exercises for “Basic programming in Python”. I will provide feedback on the hand-ins as soon as possible so feel free to hand in earlier if this is easier for your time plan.
  • 6 october: hand in preparatory assignment for “Analysis of discrete data with R”.
  • 10-11 october: physical meeting in Luleå for “Analysis of discrete data with R”.
  • 12-13 october: physical meeting in Luleå for “Analysis of continuous data with Python”.
  • 27 october: hand-in final assignment for “Analysis of discrete data with R”.
  • 3 november: hand-in final assignment for “Analysis of continuous data with Python”.
  • Note: if you are busy with e.g. fieldwork or teaching around that time we can offer some flexibility regarding the hand-in deadlines.

Teaching format

During the physical meetings, we mainly work with a number of exercises and examples from the water sector. There will also be some short lectures explaining certain topics, common problems you might encounter, or the basics of the statistical methods used in the course about R. We will spend the days in Luleå in a computer room.

You select your self which modules you would like to take, depending on interest and knowledge. Module 2 (project) you sign up for when you are in Luleå.

Module 1 P0: Basic programming in Python (2 ECTS)

Almost entirely self-study based on book (, chapters 1-14). A few exercises to be handed in digitally.

Ok to skip for people who have experience with Python. Must be completed by students with no programming experience or people with experience in other languages such as Matlab.

This course must be completed before P1 if the student does not yet have this knowledge.


Module 2 P1: Analysis of continuous data with Python (2 ECTS)

Preparatory reading. In class we focus on exercises and problems specifically related to the water sector. After the class you finalize and hand in an assignment.


Module 3 R1: Analysis of discrete data with R (2 ECTS)

Prior to meeting in person, you should complete Module 1, which consists of a series of tutorials on basic skills in R, so that we can focus on statistical analysis and graphs, including water-industry-specific examples during the in-person meeting.


Module 4: Project (2 ECTS)

You will have the opportunity to decide where to carry out a project for additional credits during the in-person meeting. A data to present the project will be decided during that meeting.

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