Advances in scientific technologies from remote sensors to genetic sequencers mean scientists are now working with huge data sets, and must be expert in the computer tools that can analyse those data. Many undergraduate science papers now require students to process and analyse real data using special programming languages like R. In this mini-course, we will help you to learn exactly those parts of R that science students need for their in-course research assignments. Class sessions combine structured presentation of new material, and hands-on coding practice with support from experienced R programmers, scientists, and educators.
There is no assessment or credit offered as part of this course.
Sign up has closed for semester 2.
The course materials are free to use and work through. If you have questions or would like assistance with R, please email rtis.training@otago.ac.nz.
The course material is free of cost and is AVAILABLE HERE
Material can be worked through on either your own machine (R and RStudio will need to be installed) or on the Virtual Student Desktop
It would be greatly appreciated if as you complete modules you fill in this three question survey https://tinyurl.com/r4ssp-module-fb which will help further iterations of the course.
What: These sessions will be structured as a workshop with content taught and some exercises available. There will also be an opportunity to get assistance with code you are working on. To get the most out of these sessions bringing your own device with access to R/RStudio is strongly recommended.
When and where: Semester 2 2023 R for Successful Student Projects (R4SSP) will be online via Zoom, 1-3pm Tuesdays.
please sign up for details
It is possible to complete the course in your own time, but the Instructor led sessions will follow this schedule:
| Date | Week | Module | Part | Topic | Instructor |
|---|---|---|---|---|---|
| Week starting 18 July | 1 | Setup | Introduce the tools: R and Rstudio | P | |
| Week starting 25 July | 2 | Data focus | 1 | Visualising Data | M |
| Week starting 1 August | 3 | Data focus | 2 | Selecting and Filtering Data | P |
| Week starting 8 August | 4 | Data focus | 3 | Summarising Data | M |
| Week starting 15 August | 5 | Data focus | 4 | Communicating Data | P |
| Week starting 22 August | 6 | Data focus | 5 | Tidying Data | M |
| Week starting 29 August | - | MID-SEMESTER | |||
| Week starting 5 September | 7 | Data focus | 6 | Combining/Joining | P |
| Week starting 12 September | 8 | Programming focus | 1 | Functions and Choices | M |
| Week starting 19 September | 9 | Programming focus | 2 | Repeating code | P |
| Week starting 26 September | 10 | Programming focus | 3 | Workflows and debugging | M |
| Week starting 3 October | — | — | — | Ask us anything | P/M |
Optional unit - Using version control with R (TBD)
During the sessions assistance for your own code projects can also be sought.
University of Otago ITS also offer free courses for students and staff for R. Descriptions and registration can be found at https://corpapp.otago.ac.nz/training/its/course/subject/research-tools/
The Carpentries is a global organisation that provides workshops to teach computational skills for researchers. Periodically we run these workshops on campus. Check out https://otagocarpentries.github.io/ for up-coming workshops run at Otago. The workshop content is also free and available to be worked through outside of the workshops. These are the R relevant workshops from The Carpentries:
R for Data Science online community is an online community created to help people learn R from the R for Data Science book by Hadley Wickham.