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 course credit or summative assessment associated with this course.
This course uses a hybrid delivery model where teaching sessions combine succinct presentations of new content with hands-on, focused coding practice in the classroom. Facilitator support is tailored to individual student need. The course comprises nine modules, delivered over 10 weeks (no session during mid-semester break). However, support is provided for any module at any time, to accommodate each student’s rate of work.
At the completion of this paper, students will be able to:
R, RStudio, and assorted RStudio packages. All required software is open source, is available online for download at no cost, and is included in the current University of Otago student computer image.
Content materials consist of digital documents (provided), online texts, online videos, and online interactive exercises (suggested), all at publicly accessible websites. Modules have associated practical exercises (provided). Students will be able to choose exemplar data sets to use in the performance of later practical exercises, ensuring that the work will be largely contextualised in each student’s preferred field of study.