Content
We will be covering the following broad topics:
- reproducible research in R (rmarkdown, knitr),
- collaborative work using git and GitHub, CD/CI,
- R code style guidelines,
- parallelization and vectorization in R,
- writing own functions – best practices,
- understanding and using the system of R classes: S3, S4, R6 and RC,
- anatomy of an R package: writing your own package from scratch,
- code debugging, profiling and optimization,
- tidy data flow with
tidyverse
, - efficient use of
magrittr
pipes, - using the language of graphics,
ggplot2
, - intro to working with maps (
ggmap2
) & interactive plots, - developing simple web applications using
shiny
, - efficient modeling
If you want to check out the course materials from 2019, you can find them here.