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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/05/technical-foundations-of-informatics.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p><a target="_blank" rel="nofollow" href="https://ischool.uw.edu/academics/informatics/what-is-informatics">Informatics</a> (or Information Science) is the practice of creating, storing, finding, manipulating and sharing information. These are all tasks that the R language was designed for, and so <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/index.html">Technical Foundations of Informatics</a>, the online course guide for the University of Washington course of the same name, also provides an excellent resource for learning those skills using R.</p>
<p><a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/"><img title="Tfoi-logo" alt="Tfoi-logo" src="http://a6.typepad.com/6a0105360ba1c6970c01bb09976f5e970d-320wi"></a></p>
<p>The course guide, co-developed by <a target="_blank" rel="nofollow" href="http://mfviz.com/#/">Michael Freeman</a> and <a target="_blank" rel="nofollow" href="http://faculty.washington.edu/joelross/">Joel Ross</a>, is a self-contained book that teaches you how to work with data using R in modern and reproducable ways. It assumes no technical background, but jumps quickly into setting up the necessary infrastructure for reproducible data science: R, RStudio, Git, an editor, and a command shell.</p>
<p>With the infrastructure in place, the remainder of the course is largely an <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/introduction-to-r.html">introduction to R</a> itself: the basic objects, functions and data types. The content focuses on what you need to know, rather than attempting to be comprehensive: for example, data frame manipulation smartly jumps straight to using the <a target="_blank" rel="nofollow" href="http://dplyr.tidyverse.org/">dplyr package</a> rather than covering the &quot;old-school&quot; techniques for working with data. If you haven't tried out dplyr yet, <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/introduction-to-the-dplyr-package.html">Chapter 11</a> is a great quick-start tutorial in its own right.</p>
<p>Similarly, for data visualization the text jumps straight to using the <a target="_blank" rel="nofollow" href="http://ggplot2.tidyverse.org/">ggplot2 package</a> rather than covering the older, base graphic techniques. It can take some effort to learn ggplot2's grammar of graphics, but that early effort pays off in the long run when it comes to creating consistently attractive, information-rich graphics. Fortunately, <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/ggplot2.html">Chapter 14</a> provides a concise introduction to the topic, and again serves as an excellent quick-start guide to ggplot2 if you haven't yet taken the plunge. There's also a chapter on using <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/plotly.html">Plotly</a> for creating interactive graphics using the ggplot2 syntax.</p>
<p>Other topics covered in the guide include: <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/introduction-to-application-programming-interfaces.html">accessing data via APIs</a>; using <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/r-markdown.html">R Markdown</a> to create documents and websites using R; working with others via the <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/git-collaboration.html">Git</a> source code control system; and creating <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/shiny.html">interactive applications with Shiny</a>.</p>
<p>Overall the course guide represents an excellent and concise introduction to the modern way of working with R. Although the course assumes no technical background, it does jump into the deep end quite quickly, and focuses on some advanced topics while omitting some basic areas of R. But by only showing one way of achieving various goals in Informatics, the book should get you up to speed with the most modern ways of using R quite quickly. The course guide is freely available to everyone at the link below.</p>
<p>University of Washington Informatics: <a target="_blank" rel="nofollow" href="https://info201-s17.github.io/book/">Technical Foundations of Informatics</a></p>
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