Ten simple rules for teaching yourself R

[...]in a recent survey of science educators, the vast majority of respondents rated data skills (analysis and visualization) as extremely or very important for undergraduate students, but respondents particularly from bachelors-granting institutions also listed “outside of coursework” as the most likely place for students to learn such skills [3]. Importantly, we write this list of strategies and resources not as the voice of authority of the vast and diverse universe of R users, but simply as a group of quantitative-minded mostly ecologists, generally located in universities across Canada, who have all learned R largely without formal instruction. [...]the Quebec Centre for Biodiversity Science (QCBS) R Workshop Series offers introductory and advanced workshops on data visualization, linear models, multivariate analyses, and more, in both English and French, with freely available slides, code, and companion books on their website. The Coding Club from the University of Edinburgh offers a wide breadth of courses for ecologists and environmental scientists, ranging from data manipulation and statistics to geospatial analysis and machine learning.