Course Syllabus
Welcome to the course!
If you are accepted to the course, please register on Ladok before the date specified in the welcome letter. Otherwise you will lose your place on the course.
If you are registered and want to get started with the course, head over to Modules to find the course material and Assignments to find the assignments. If you have any questions, ask in Discussions or send a PM or email to one of the teachers.
Course information
The course starts on June 8th and relies mostly on recorded material and self studies with opportunities for non-mandatory online supervision (Zoom). Important information before the course starts can be found in the welcome letter. Once you are registered on the course, you can access the course material under Modules here on Canvas. To complete the course, there are three mandatory assignments, which can be found under Assignments.
The course requires you to install R and RStudio on your computer. Instructions on how to install R and RStudio can be found https://posit.co/download/rstudio-desktop/. If you encounter problems with installing R and/or RStudio you can try out Posit Cloud, a webb-based version of RStudio that you can run in your browser. The free plan offers 25 hour per month, which should be sufficient for at least getting started with the course.
Suggestion for students taking both Introduction to R and Data Analytics with R (DAwR):
In the first week (8th - 12th June), do the first assignment (DataCamp) in Introduction to R (and skip the introduction to R part in DAwR). In the second week (15th - 18th June), do the first assignment in DAwR. This gets you started in both courses. After this, we suggest studying the courses in parallel, keeping the deadlines of both courses in mind.
Teachers
Filip Edström, supported by Hugo Morvan and Joakim Wallmark
If you have any questions, please send Filip an email with the subject starting with [DAwR]. It helps us to keep track of course related emails and respond faster. You may write in English or Swedish in emails (assignments are in English only).
Course literature
Lecture notes (available at https://fied0002-dawr-lecture-notes.share.connect.posit.cloud/
R for data science (R4DS) : import, tidy, transform, visualize and model data (2nd edition, available free online at https://r4ds.hadley.nz/)
Wickham Hadley, Mine Çetinkaya-Rundel, Grolemund Garrett
2023
ISBN: 1492097403
Once the course starts, see Course literature R for Data Science (R4DS) with reading instructions for reading instructions.