TL; DR

Free training from SAS: "SAS Programming for R Users." Check the available Live Web offerings and register for one that fits your schedule. Or use the free e-Learning version and learn at your own pace. The complete course materials are on the SAS Software GitHub space and you can practice with the free SAS University Edition software.

Update April 10, 2017: SAS has built an e-Learning version of this course, and it's available for free. Use the course lecture and demos, combined with exercises and free SAS software (SAS University Edition) to apply your R skills to the SAS programming language.

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The details: how R programmers can learn SAS for free

As much as I would love for SAS customers to use SAS to the exclusion of everything else, that rarely happens. Every time I visit a SAS customer, I hear about the other non-SAS tools that they use alongside SAS and their integration points. The most popular of these include desktop tools such as Microsoft Excel, or enterprise databases from other vendors. But increasingly, I hear from users who dabble in open source tools such as Python and R, or who work with other teams that use those tools.

Programmers tend to favor the programming languages that they know. When you learn a new programming language, your experience is colored by inevitable comparisons with the languages you've already mastered. If you work with R coders who want to learn SAS, you should consider that they probably won't learn SAS the same way that you did.

A SAS programming course for experienced programmers

The traditional way to learn SAS begins with the DATA step, where you learn how to read files, how to write files, about the program data vector, and basically how the DATA step "thinks". Then you move on to the various procedures for descriptive stats, reporting, and maybe even some graphing. While this approach can make you productive with simple tasks quickly, to an R coder this might feel too much like "starting over." That's why R programmers (or even MATLAB or Stata users) need an approach that leverages what they already know to hit the ground running.

That's the thinking behind the new SAS Programming for R Users course. This course does not start with the basics about statistics or the importance of data prep -- the assumption is that you already know that. Instead, you'll get hands-on experience with SAS/IML -- a statistical matrix language that will certainly feel familiar to R users. You'll eventually get to the DATA step and other procedures, of course -- and these will open new worlds for you -- but you'll learn to be productive quickly using the skills you already have. (You can read more about the genesis of the course from its creator and main instructor, Jordan Bakerman.)

The course centers around classic and real statistical problems, from Bayesian logistic regression to the Monty Hall problem. If you don't know your statistics, you might feel that you're swimming in waters over your head. But if you're comfortable with the concepts, you should feel right at home. (If you're just beginning with statistics, SAS offers this different free e-learning course.)

"SAS Programming for R Users" also shows you how to use SAS and R together, submitting R code from within your SAS program. That's made possible by a special connection between SAS/IML and R -- something that SAS has supported for years.

This is a free instructor-led course that's offered in Live Web format. "Live Web" means that you connect from your desk at home or work, tune into the lecture and demos, and then practice your skills on a hosted classroom environment. It's also available as self-paced e-Learning, with lecture, demo, and exercises. And this course is free -- costing you only your time. Check out the SAS Training site to find an offering that meets your schedule (or to start the e-Learning immediately).

Find the course materials on GitHub, right now

What if you can't find a Live Web offering that meets your schedule? In the spirit of openness, the SAS Training team has published the complete course materials on GitHub. You'll find the course notes (over 600 pages), data sets, and over 80 SAS programs to support the course exercises. You can use the free SAS University Edition to try the course exercises yourself and practice with the software. (The only part that you can't practice is the "submit to R" lessons, because the SAS University Edition doesn't support the connection to R.)