在數(shù)據(jù)科學(xué)領(lǐng)域，R是僅次于Python的第二大常用工具洛退。熟練掌握R的使用是在你專業(yè)領(lǐng)域力拔頭籌（“到處去浪”）的法寶碌廓。以下就是一些給你專業(yè)助攻的免費(fèi)資源。
平臺(tái)和文檔
r-bloggers.com: R-bloggers is a collection of blogs designed by R experts that covers a wide range of R topics. No matter what you’re curious about or have an issue with, R-bloggers has it covered.
免費(fèi)書
R for Data Science: This classic handbook provides resources and documentation. It’s available for free on the website, or you can purchase a physical copy from Amazon.
Hands-on Programming with R: Garrett Grolemund’s classic is a practical, hands-on approach to R programming. It gives you the instruction you need plus practical programming skills to begin with R right from the very beginning.
免費(fèi)課程
Codecademy: Codecademy’s mission is to bring development knowledge even to beginners, and its R offers are no different. While many of the lessons will require a membership, it does offer a basic set of courses to get you started.
edX.org: EdX offers a range of free R courses to get you started, but we recommend starting with
Microsoft’s Introduction to R for Data Science for a comprehensive overview. The courses cost nothing and are offered asynchronously. Some do come with official certification for a fee.
面向開(kāi)發(fā)者的免費(fèi)R資源
If you’ve already got some development experience under your belt, these resources could be a great way to get started with R by utilizing your current experience. Even better, they’re free.
平臺(tái)和文檔
storybench.com: Storybench is an experiential learning platform designed to provide exercises in digital storytelling. They offer projects in R, most notably “How to Explore Correlations in R.” Once you’ve gotten the basics, the next logical step is to take on projects for hands-on learning.
免費(fèi)書
R Programming for Data Science: This option is available for free (though you can choose to donate in support of the project). It offers full resources for learning R and understanding key data science principles. If you upgrade the package, the online book comes with a full video suite.
Text Mining with R: Another book available for free on the website, this option offers a targeted approach to text mining with a full Github repository as support.
R in Action: Another entirely free resource for business developers. If you’ve already got an established career in development in the business world, this could be an excellent resource for getting started with R in the business world.
免費(fèi)課程
Coursera: Johns Hopkins’s popular partnership with Coursera, “Data Science, Foundations Using R” is a great way for developers to build skills to break into the field of Data Science.edX + Harvard: X Series Program in Data Analysis for Life Sciences is a course series designed to implement both learning R and real-life projects for a full learning experience. You can upgrade to an official learning certificate for a fee or take the individual courses for free.
面向小白的付費(fèi)資源
Sometimes, you’ve got to invest a little in your learning experience. Here are a couple of things that can really jumpstart your R-programming skills if you’ve got some wiggle room in your budget.
Getting Started with R: A primer on using R for the biological sciences. It contains valuable information for getting started on statistical analysis using the R programming language.
flowingdata.com: Flowingdata is a membership site designed to elevate your visualizations. It’s another excellent way to get experiential learning with R projects.
Rstudio: It’s not cheap, but if you’re serious about making a career in R, you’ll want to get it. Save up and invest. They do, however, have a series of free webinars you can peruse.
額外福利! 更多的博客和即時(shí)簡(jiǎn)訊
https://blog.revolutionanalytics.com/r/ : Blog designed to highlight milestones in Data Science and includes a range of topics including both R and Python for you multilingual developers out there.
https://journal.r-project.org/: Open access, refereed journal detailing the latest in R-programming news and projects. Papers have a focus on accessibility, and the articles are tended to reach a wide audience.
https://morningcupofcoding.com/: Offers a wide range of curated coding articles, including R programming. Check their back issues for articles of interest.
opendatascience.com: ODSC’s general weekly newsletter provides members with trending topics in the fields of modeling, tools & platforms, and more.
