On-site R Training Courses
Revolution Analytics offers custom training courses for any size group, to be presented at your location by our experienced instructors. All classes are one day in length unless designated otherwise. Contact Revolution Analytics for pricing and scheduling information.
Implementing Web Services using RevoDeployR
Revolution Analytics DeployR is designed for R users and IT professionals who are interested in learning how to deploy R applications on a server for access by client applications through a web services API. The class uses a combination of lecture and labs to instruct students on how to install, configure, and manage a DeployR server instance. In addition, students will learn considerations for writing web services-based R applications, how to install and manage them within the DeployR server environment, and lastly how to access them through client-based API’s. Implementing Web Services using RevoDeployR Course Outline
Introduction to R
This course provides users new to R an overview of the R language. We cover the basics of R programming, data manipulation, graphics, and data analysis. The course also reviews technical aspects of R installations, as well as key efficiency concepts to optimize R programs. It is a hands-on course filled with real data and examples, case studies, and in-class mini projects. Introduction to R Course Outline
Introduction to R for SAS Users
Many R users are new to R, but not new to analytic programming. Experienced SAS users will find that R has some similarities with SAS, but is very different in many ways and requires a different mindset to master. Once the basic differences are understood, however, SAS users will find the power and flexibility of R’s object-oriented framework readily apparent. This course provides a foundation for programming in R specifically for those familiar with SAS. Knowledge of SAS and basic data analysis concepts is assumed. Introduction to R for SAS Users Course Outline
Introduction to Rattle for Data Mining
Data mining delivers insights, patterns, and descriptive and predictive models from the large amounts of data available today in many organizations. R provides a powerful platform for data mining. However, scripting and programming is sometimes a challenge for data analysts moving into data mining. The Rattle (R Analytical Tool To Learn Easily) package provides a graphical user interface specifically for data mining using R. It has been developed specifically to ease the transition from basic data mining, as necessarily offered by GUIs, to sophisticated data analyses using a powerful statistical language. This course focuses on usage of Rattle as a tool for data mining and not on data mining techniques. Introduction to Rattle for Data Mining Course Outline.
Introduction to R-Commander
The Rcmdr package provides a basic-statistics graphical user interface to R called the “R Commander.”
R Commander is designed to support an easy to use, cross-platform GUI for basic-statistics and to render the relationship between choices made in the GUI and the R commands that they generate. This course helps experienced statisticians to transition to R, without having to remember the names and arguments of commands, thus decreasing the chances of syntax and typing errors. The course focuses on usage of R Commander and not on the statistical techniques. Introduction to R-Commander Course Outline.
Parallel Programming in R
We are at the beginning of the multicore era. Computers will have increasingly many cores (processors). To take advantage of this industry wide shift in architecture, we need to use parallel computing.
This course presents an overview of techniques for parallel computing with R on computer clusters, multi-core systems or in grid computing. The class uses a combination of lecture and labs to instruct students on how to effectively use and script parallel programming packages in R. Parallel Programming in R Course Outline
Predictive Modeling & Data Mining with R
This course covers more advanced topics in using R for predictive modeling and data mining. We cover regression modeling including logistic regression, diagnostics and prediction, generalized linear models, and data mining procedures such as trees and neural nets, and more. Add-on R packages such as MASS, party, and nnet that include many useful statistics and modeling functions are covered. This course is a must for statisticians and modelers who are new to R. Knowledge of the R language, basic statistics, and concepts of predictive modeling is assumed. Predictive Modeling & Data Mining with R Course Outline
Taking on Big Data using RevoScaleR
This course is designed for R users who have mastered the basics of R and are interested in learning how to take advantage of the capabilities of Revolution Analytics' ScaleR package for high performance analytics on datasets that exceed the normal physical memory limits of R. The class uses a combination of lecture and lab time to instruct students on how to effectively use and script ScaleR functions for big data analyses. In addition, students will learn how to visualize the results of ScaleR analyses through use of such graphics packages as Lattice. Taking on Big Data using RevoScaleR Course Outline
Visualization in R with ggplot2
In this course, participants will learn how to use the ggplot R Project to make, format, label and adjust graphs using R. The ggplot2 Project, created by Hadley Wickham, is named after the term "Grammar of Graphics," which was coined by Leland Wilkinson (creator of Systat). This "grammar of graphics" is a system of describing and organizing the fundamental components of a graph and the process of creating a graph. Using ggplot2, participants will learn how to design and implement graphs in an efficient, elegant and systematic manner, following principles of general good graphing practice. Visualization in R with ggplot2 Course Outline.
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