An R Programming course from Microsoft, in collaboration with the Technical University of Denmark, started last week on the edX platform. If you want to get up to speed programming in R there's still time to catch up.

This a four-week course that started on April 19th with an estimated workload of 4-8 hours per week. The videos for all four of its modules are now online and its quizzes and labs, all of which are also available are all due before June 27th, 2016. If you want a Verified Certificate the deadline for upgrading  in May 15th. This costs $49 and you'll need a webcam and a government-issued photo ID, which as we discovered with the Microsoft C# course requires your signature to be on the same page as your photo. If you are happy with an Honor Certificate the course is completely free.

The hands-on course is taught by statistician Anders Stockmarr who is an associate professor at the Technical University of Denmark. The course uses Microsoft R Open, the enhanced distribution of R from Microsoft. Based on R it includes capabilities for improved performance and reproducibility. Like R, Microsoft R Open is open source and free to download, use and share.

Over the course of four weeks participants will learn about R’s data structures and syntaxes, how to read and write data from a local file to a cloud-hosted database, working with data, getting summaries, and transforming them to fit your needs. The course also covers how to perform predictive analytics using R and how to create visualizations using the popular ggplot2 package.

Prerequisites for the course include a background in high-school level mathematics, and some exposure to programming language. Those who don't have any programming experience are recommended to do the self-paced, and therefore currently available, course DAT204x: Introduction to R for Data Science.

This is four-week course with a workload of 2 hours per week. It takes variables and basic operations as its starting point and goes on to cover data structures such as vectors, matrices, data frames and lists. The final section goes into the graphical capabilities of R for creating data visualizations. Throughout the course participants practice their newly acquired skills through interactive in-browser coding challenges using the DataCamp platform.

With R becoming the language of choice for anything to do with data science and statistics this free opportunity on edX to get to know the language seems worthwhile. 

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