title: "Resources"

* [What classes should I take if I want to become a data scientist?](https://www.quora.com/What-classes-should-I-take-if-I-want-to-become-a-data-scientist)

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* [A very short introduction to R](https://cran.r-project.org/doc/contrib/Torfs+Brauer-Short-R-Intro.pdf)

* [R Markdown Cheat Sheet (PDF)](http://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf), a quick guide to the most commonly used markdown syntax, knitr options, and output formats.

* [R Markdown Reference Guide (PDF)](http://www.rstudio.com/wp-content/uploads/2015/03/rmarkdown-reference.pdf), a more comprehensive reference guide to markdown, knitr, and output format options.

* [Infographic Layout](http://www.r-bloggers.com/r-how-to-layout-and-design-an-infographic/)

For even more in-depth documentation see:

* [Advanced R](http://adv-r.had.co.nz) book for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as it explains some of R’s quirks and shows how some parts that seem horrible do have a positive side.

* The website for the [knitr package](http://yihui.name/knitr/). Knitr is an extremely powerful tool for dynamic content generation and the website has a wealth of documentation and examples to help you utilize it to its full potential.

* A detailed overview about writing your own [R Packages](http://r-pkgs.had.co.nz) by Hadley Wickham.