R is one of the most popular and fastest growing languages for statistical analyses and predictive anayltics. Unlike proprietary software such as SPSS, SAS, and MatLab, R is free, open source, and has an huge community of developers. For these reasons, R is often the programming language of choice for academic research and industry titans such as Google, Apple and Facebook. In this course, you will learn R from the ‘ground-up’ in an intensive 4-day course covering 4 different modules. In the first module, you will learn the basics of the R language, from loading external data as new objects, to doing basic calculations, to loading new packages. In the second module, you will learn an overview of R’s most common statistical functions and packages, from basic descriptive statistics, to hypothesis tests such as t-tests, ANOVA and regression, to Bayesian statistics and advanced machine learning algorithms. In the third module, you will learn how to make elegant, modern data visualisations, from histograms, barplots and scatterplots, to network plots and maps, to interactive web-based visualizations with Shiny. Finally, in the fourth module, you will learn how to write clearly structured and efficient code, supplemented with C++ and parallel functions, how to write and share reproducible documents with R Markdown, and how to share your code on popular code sharing platforms such as GitHub and the Open Science Framework.