learnr::run_tutorial(
name = "ProjectOrga",
package = "DataScienceExercises",
shiny_args=list("launch.browser"=TRUE))🗓️ Session 3: Project management and recap
This is one of the most underestimated topics. In this session you learn how to adequately set up your working environment on your computer. This means where you should save which files, which directory structure you should use, and how to point the computer to other files on your computer. While this sounds boring at first, taking seriously the insights from this session will save you tons of hours of frustration in the future!
🛠️ Recap: writing your own functions
Open the slides in a separate tab
Open the slides, click the ☰ button in the bottom left corner, and choose Tools → PDF Export Mode. Then print the page (Cmd/Ctrl + P) and save it as a PDF.
In the recap part of the session we discussed the topic of writing functions together, alongside two examples.
👨🏫 Lecture Slides on Project Management
Open the slides in a separate tab
Open the slides, click the ☰ button in the bottom left corner, and choose Tools → PDF Export Mode. Then print the page (Cmd/Ctrl + P) and save it as a PDF.
🎥 Lecture videos
Currently, no videos are available for this session. Check out the resource Setting Up an R Project on Method and Inquiry instead.
📚 Mandatory Reading
- Setting Up an R Project on Method and Inquiry (Gräbner-Radkowitsch 2026b)
- On functions: Object Types in R I: Functions on Method and Inquiry (Gräbner-Radkowitsch 2026a)
Further Reading
While we do not cover this in this course, I highly recommend learning the version control system Git. Personally, I can recommend the following:
- Very concise introduction to Git
- Introduction to GitHub: GitHub skills and the official docs
✍️ Coursework
- Do the exercises
ProjectOrgafrom theDataScienceExercisespackage that refer to setting up an R project - If you still have problems with R Packages, re-read the respective section of the resource from session 2