R is a powerful language for data science in many disciplines of research with a steep learning curve. The tidyverse group of packages provide a dialect that greatly simplifies data importing, cleaning, processing, and visualization as well as providing reproducible workflows, replacing many intricacies of R with clear and easy to learn syntax. The course will be run on Thursday, 7 and Friday 8 May and Monday 10 and Tuesday 11 May 17th, 2020.
The four day course provides a complete introduction to data science in R with the tidyverse. The course will not go deep into statistics but rather getting data ready, some exploratory analysis, visualization and handling models. Preparing data takes up to 90% of the time spent in analysis — speeding this up is the mission of this course.
This course will take place either online or on-site depending on the current situation.
Participants should have basic experience in R or intermediate experience in other programming environments for data analysis such as Matlab, Octave or Python. This is not a beginners’ course to programming.
Day 1 will review the basics of R and loading data via the readr package as well as Markdown. Day 2 will introduce tidying and organising data via the tidyr and dplyr packages as well as ggplot2 for visualisation. Day 3 will look at functional programming tools using the purrr package, which greatly simplifies repeating operations. Many statistical packages have complicated and idiosyncratic data structures. The broom package helps to convert them to consistent data structures. Participants are encouraged to bring their own data for analysis, convert existing code to tidyverse or perform a project on Day 4. Students will receive 2 ECTS in category 1, which requires handing in a short report in Rmarkdown at the end of the course. Students that completed this course in the previous years are not eligible for ECTS.
Please see the detailed instructions on our Course website
Registration is open. The course is limited to 30 participants.
Aurélien GINOLHAC (LSRU) and Roland KRAUSE (ELIXIR-LU/LCSB)
Maison du Nombre (MNO)
University of Luxembourg
6, avenue de la Fonte