Merge pull request datasciencemasters#12 from ssaeger/master

I added Kaggle and a Tutorial to learn R

README.md

@@ -110,6 +110,7 @@ Start here.
  * Viz and Elegant Graphics in R: ggplot2 [Springer / Book](http://www.springer.com/statistics/computational+statistics/book/978-0-387-98140-6)
  * Machine Learning in R [Tutorial](http://blog.revolutionanalytics.com/2009/09/machine-learning-in-r-in-a-nutshell.html)
  * Guide to Getting Started in Machine Learning [Tutorial](http://abeautifulwww.com/2009/10/11/guide-to-getting-started-in-machine-learning/)
+ * Learn R & Become a Data Analyst [Tutorial](https://www.datacamp.com/)
 
 * **R** (Libraries)
 * Natural Language Toolkit [OpenNLP](http://cran.r-project.org/web/packages/openNLP/index.html)
@@ -146,6 +147,9 @@ Start here.
 * Rice University's Data Viz class [Rice University] (http://had.co.nz/stat645/)
 * Interactive Data Visualization Book [O'Reilley] (http://chimera.labs.oreilly.com/books/1230000000345/index.html)
 
+### Sources for Data Set:
+* Competitions between Data Scientists on new datasets [Kaggle] (https://www.kaggle.com/)
+
 ### A Note About Direction
 This is an introduction geared toward those with at least **a minimum understanding of programming**, and (perhaps obviously) an interest in the components of Data Science (like statistics and distributed computing).
 Out of personal preference and need for focus, I geared the original curriculum toward **Python tools and resources**, so I've explicitly marked when resources use other tools to teach conceptual material (like R)