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Microsoft R for Data Science Workshop

Join the chat at https://gitter.im/mr4ds/Lobby

Welcome to the Microsoft R for Data Science Course Repository. You can find the latest materials from the workshop here, and links for course materials from prior iterations of the course ca be found in the version pane. While this course is intended for data scientists and analysts interested in the Microsoft R programming stack (i.e., Microsoft employees in the Algorithms and Data Science group), other programmers might find the material useful as well.

Review instructions:

For Instructors:

  1. Please view the instructions given in the Instructor-Resources folder.

For Students:

  1. The rendered course materials are available in the Student-Resources folder.

During class, pleae review the links and information below:

Class Links

  • course webpage
  • gitter page
    • we are going to try and use gitter as a discussion forum for anything related to the course materials, and Microsoft R Server more generally
  • Course wiki
    • the course wiki contains some instructions on how to install the class applications locally
    • it also contains the course syllabus
  • Class Playlist
    • As your instructor, I'll also be your workshop dj. Feel free to make requests.

Course Outline

Please refer to the course syllabus for the full syllabus. The goal of this course is to cover the following modules, although some of the latter modules may be repalced for a hackathon/office hours.

  • Topics:
    • R Fundamentals
    • Data Manipulation with dplyr
    • Data Manipulation with dplyrXdf
    • Modeling and Scoring with Microsoft R
    • Parallel Computing with the RevoScaleR package
    • Deploying Models with the AzureML package
    • RxSpark and R APIs for Spark


We will use DSVMs (Data Science Virtual Machines) from the Azure marketplace to run the course materials. For the Spark training, we will use Spark HDInsight Premium clusters, also from Azure. If you are interested in running these materials in a different environment, see the course wiki for instructions.

You can download R client locally using the Dockerfile here.


  • I'll send you your credentials by email