RSS01.D1 R for Advanced Users
The advanced R course covers topics that are usually out of scope in the intro to R courses or quantitative methods trainings. The focus of the course is to provide a deeper understanding of R and leverage this to write more efficient R code. We will look at how to do functional programming and object oriented programming with R. This also includes deepening and enriching existing knowledge about parts of R (about vectors, control flows, etc.).
During the course, the participants will learn how to write (better) functions, work with functionals (e.g.: base::lapply, purrr::map), debug, and optimize code. These skills are useful to create code that is more robust, re-usable and modifiable and hopefully faster. Getting comfortable writing functions opens up many possibilities: customizing already existing approaches to specific needs, implementing new techniques, and most importantly: cutting back on error prone copy pasting of code.
The course will also cover building an R package and hosting it on GitHub. The current R package ecosystem makes building packages a streamlined experience. Building personal R packages is taking the Don’t Repeat Yourself idea a step further by eliminating the need to copy functions from one project to another by storing them in a package.
Similarly, using version control is a useful collaborative skill. During the course we will learn the basics of git and how to make version control a natural part of an R workflow. Using git is helpful to keep track of changes in code, share code with collaborators and to have a repository which can be used to reproduce the analysis or research results.
In addition to these larger topics there are some smaller quality of life titbits that the course will also cover:
- Using APIs to get data into R
- Creating custom ggplot2 themes
- Getting the most out of Rmarkdown
- Ways to deal with large datasets
|19 June 2023 - 23 June 2023|
Early Bird Regular: €895 (application deadline* April 1st)
|Scholarships and discounts||Find more information here|
*Your application is only completed when the course fee has been paid
|Course leader||Akos Mate|
|Level of participant||
|Admission requirements||Basics of R knowledge is assumed, that are usually covered in intro classes. This includes some knowledge about vectors in R, data frames, how to load data and use R for data analysis.|
|Mode of Study||On Campus|
|ECTS||2 or 4 Find more information here|