Inspired by this article i thought about gather here all multimedia resources that i know to learn use R. Today there is a lot of online courses, some MOOC’s too, that offer reasonable resources to start with R.
I will just list the materials in sequence and offer my evaluation about them. Of course your evaluation can be different; this case fell free to comment. In the future i can update the material. Let’s begin:
This course was offered multiple times from 2012 to 2014. I did the course at 2013 and the course was very well formatted, with good exercises and lots of resources. It was offered on Coursera platform, that i particularly think excellent, and take an average effort to finish. There is quiz questions and program assignments. The course is free.
This course is offered at coursera too, from the same instructor as Computing for Data Analysis. According to course syllabus: “The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples.”
Well, once that there is now the coursera specializations, i thinks that this course is “Computing for Data Analysis” rebuilded. SO, if you already did the first course i don’t see any advantage doing this one, unless you want to get the specialization certificate.
This course was about the practical aspect of data analysis with R. All activities was in R, but the course wasn’t about R itself. But it was very good and you can learn a lot of R with it. The course is free and offered on Cousera platform.
OBS: Both, Computing for Data Analysis and Data Analysis, can be replaced for other courses on coursera specialization. I won’t comment now about these new courses because some of them are being offered now and other will be offered on the next months. Anyway both course materials are avaliable on youtube.
This course is being offered at bigdatauniversity platform. The course is a good starting point but i don’t this platform like so much. But the pros of this course is that you can do it on your pace and it have less material to cover. It’s a quick introduction to R.
This course will be too offered at bigdatauniversity, but it’s not avaliable right now. It will be recorded, and you can participate through live stream from bigdatauniversity, and released on that platform. The course doesn’t have a syllabus available, but i think that the content of this book, will probably be the topics discussed.
Rattle is a GUI for datamining that uses R as backend. It’s very intuitive and resembles Weka interface. While it’s not as flexible as use R directly it provides a quick way to explore and buid models with R. With Rattle() every step taken is saved on a log that you can use as scripts to automate tasks.
This course is too being offered at bigdatauniversity. It’s supposing you have some R skills and is about the use of databases with R. It uses IBM DB2 specifically, but you can apply the concepts to others databases as well. It’s free and i liked it.
I’m taking this course right now and i will write a post specifically about it. BUT, just to clarify, it’s a course about machine learning (or statiscical learning if you want) based on the introductory book Introduction to Statistical Learning.
The course isn’t about R itself but all the techniques are implemented using R. This course is a easy way to read the book. The course is free and is offered at openedX platform, that is a wonderful platform for MOOCs.
This course is offered at Udemy platform. Udemy is a great platform both to create your own course as to take a course. The course is not free, but it has good reviews of users and you have 30 days to evaluate the material and be refounded.
The author claim that you can learn the basics with 2 days of course.
This course will be released at september on edX. So no further comments.
This is another Udemy course. Worth of checking.
Obs: Coursera will offer Developing Data Products for free next june. This course is about the very same topics. So maybe it’s worth wait.