在当下信息爆炸的时代，唯一不缺的就是各种学习资源：

《R 语言资料卡片》中文版 https://github.com/sunbjt/r_reference
《R导论》中文版 https://github.com/DingGuohui/R-intro-cn
《R 语言高频问题》https://cran.r-project.org/doc/contrib/Liu-FAQ.pdf 由刘思喆收集自中文论坛，非 Kurt Hornik 维护的官方文档

适合入门的书籍：

《Exploratory Data Analysis with R》探索性分析与 R 语言 Roger D. Peng https://bookdown.org/rdpeng/exdata/
《R Programming for Data Science》数据科学中的 R 语言 Roger D. Peng https://bookdown.org/rdpeng/rprogdatascience/
《Efficient R programming》高效的 R 语言编程 Colin Gillespie 和 Robin Lovelace https://csgillespie.github.io/efficientR/
《An Introduction to R》 R 语言入门 Alex Douglas, Deon Roos, Francesca Mancini, Ana Couto 和 David Lusseau https://intro2r.com/
《The Book of R》https://web.itu.edu.tr/_tokerem/The_Book_of_R.pdf
《The Art of R Programming》http://heather.cs.ucdavis.edu/_matloff/132/NSPpart.pdf
《Hands-On Programming with R》 https://web.itu.edu.tr/_tokerem/Hands-On_R.pdf
《Learning R》 https://web.itu.edu.tr/_tokerem/Learning_R.pdf
《R for Data Science》 http://r4ds.had.co.nz/
《Data Science for Psychologists》心理学家的数据科学 https://bookdown.org/hneth/ds4psy/
《Big Book of R》R 语言学习资源集散地 https://bigbookofr.netlify.app/
《Data Science in Education Using R》数据科学在教育领域中的应用 https://datascienceineducation.com/
《Statistical Modeling and Computation for Educational Scientists》统计建模和计算在教育科学中的应用 https://zief0002.github.io/modeling/

与数据可视化相关：

《ggplot2: Elegant Graphics for Data Analysis, 3rd》数据分析与图形艺术 Hadley Wickham https://ggplot2-book.org/
《Fundamentals of Data Visualization》数据可视化精要 Claus O. Wilke https://serialmentor.com/dataviz/
《Interactive web-based data visualization with R, plotly, and shiny》交互式数据可视化 Carson Sievert https://plotly-r.com/
《Data Visualization: A Practical Introduction》数据可视化：实践指南 Kieran Healy https://socviz.co/

与编程开发相关：

与写书、建站相关：

bookdown: Authoring Books and Technical Documents with R Markdown https://bookdown.org/yihui/bookdown/
blogdown: Creating Websites with R Markdown https://bookdown.org/yihui/blogdown/
R Markdown: The Definitive Guide https://bookdown.org/yihui/rmarkdown/
Reproducible Research with R and RStudio https://github.com/christophergandrud/Rep-Res-Book

与 shiny 相关：

《Engineering Production-Grade Shiny Apps》 Colin Fay, Sébastien Rochette, Vincent Guyader 和 Cervan Girard https://engineering-shiny.org/
《Mastering Shiny》Hadley Wickham https://mastering-shiny.org/

与统计推断相关：

《Computer Age Statistical Inference: Algorithms, Evidence and Data Science》 Bradley Efron 和 Trevor Hastie https://web.stanford.edu/_hastie/CASI/
《Spatio-Temporal Statistics with R》 Christopher K. Wikle, Andrew Zammit-Mangion, and Noel Cressie https://spacetimewithr.org/
《Geocomputation with R》 Robin Lovelace, Jakub Nowosad, Jannes Muenchow https://geocompr.robinlovelace.net/
《Bayesian inference with INLA》Virgilio Gómez-Rubio https://becarioprecario.bitbucket.io/inla-gitbook/
《Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA》Elias T. Krainski, Virgilio Gómez-Rubio, Haakon Bakka, Amanda Lenzi, Daniela Castro-Camilo, Daniel Simpson, Finn Lindgren and Håvard Rue https://becarioprecario.bitbucket.io/spde-gitbook/
《Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny》 Paula Moraga https://www.paulamoraga.com/book-geospatial/
《Spatial Data Science》 Edzer Pebesma and Roger Bivand https://www.r-spatial.org/book
《All Models Are Wrong: Concepts of Statistical Learning》Gaston Sanchez and Ethan Marzban https://allmodelsarewrong.github.io/
《Statistical Inference via Data Science: A ModernDive into R and the Tidyverse》 Chester Ismay and Albert Y. Kim https://moderndive.com/
《Statistical Learning From A Regression Perspective》 Richard A. Berk

与机器学习相关：

以及课程资源：

CS229: Machine Learning 机器学习课程 http://cs229.stanford.edu/
Statistical Learning 统计学习课程 Trevor Hastie and Rob Tibshirani https://www.dataschool.io/15-hours-of-expert-machine-learning-videos/
Data wrangling, exploration, and analysis with R 数据加工、探索和分析 Jenny Bryan https://stat545.com/

还有各类食谱：

《R Cookbook, 2nd》R 语言食谱 James (JD) Long 和 Paul Teetor https://rc2e.com/ 书稿源码
《R Graphics Cookbook, 2nd》 R 绘图食谱 Winston Chang https://r-graphics.org/ 书稿源码
《R Markdown Cookbook》R Markdown 食谱 Yihui Xie、 Christophe Dervieux 和 Emily Riederer https://bookdown.org/yihui/rmarkdown-cookbook/ 书稿源码

以及中外博客：

除了 R 语言，我们还需要掌握一点和命令行相关的东西，比如 Bash 和 Makefile 等。

以及了解一些大数据处理工具