Introduction to Revolution R Enterprise For Big Data Analytics on

November 18, 2014

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

by Jeremy Reynolds
Senior R Trainer, Revolution Analytics

Last week, Revolution Analytics released its first massive open, online course through a partnership with Introduction to Revolution R Enterprise for Big Data Analytics. You can sign up for the free course here.

This course provides a look at some of the tools provided by the RevoScaleR package that ships with Revolution R Enterprise. The course and the interactive training framework provided by the platform allow you to get a feel for how you can manipulate, visualize, and analyze large datasets with RevoScaleR.


There are four “chapters” within the course:

  • Chapter 1 introduces the RevoScaleR package. Within the chapter, we discuss the challenges associated with big data and how the functions and algorithms in RevoScaleR address them. We walk through an example in which we demonstrate the use of several core RevoScaleR functions, and we provide exercises in which you can use the RevoScaleR to create your first linear model on big data.
  • Chapter 2 provides details for some of the RevoScaleR functions used to explore large datasets. We demonstrate how you can use these functions to summarize, cross-tabulate, and visualize variables in large datasets, and we provide hands-on exercises where you can practice with them.
  • Chapter 3 covers the RevoScaleR functions used to manipulate and transform large datasets. We demonstrate how you can use these functions to perform simple and complex transformations. We provide a set of interactive exercises that allow you to practice creating transformed variables and to explore how chunking algorithms impact the ways in which you need to process data.
  • Chapter 4 concentrates on the analysis of larte data sets. We demonstrate how to use RevoScaleR functions to build statistical and machine learning models on large data sets. Here, we cover linear and logistic regression, k-means clustering, and decision tree estimation. For each kind of analysis, there are hands-on exercises in which you can explore some of the flexibility and power associated with the functions.

We are very excited about our partnership with — the platform provides a unique, hands-on training environment in which you can practice in a live R environment, and you can “learn by doing.” We are diligently working to create more extensive content, including courses on the Fundamentals of the R Programming Language, Introductory Statistics with Revolution R Enterprise, Predictive Modeling, and Advanced R Programming. Stay tuned for more!

DataCamp: Introduction to Revolution R Enterprise for Big Data Analytics

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