Learning R at coursera.org: computer for data analysis
A few weeks ago, I finished a course titled Computing for Data Analysis, at coursera.org, because I wanted to learn about R, a free software environment for statistical computing and graphics, with its own programming language. This is the second course trying to learn R, and the first one “no compulsory” (I took the previous one at University of Cordoba, where I did a MSc on Distributed Renovable Energy).
Computing for data analysis
This course is perfect for introducing to R, although my expextations came down at the end (it’s a personal opinion, of course). This is the first course I took at coursera.org, and my note is 8.
The video quality and the knowledge of the instructor is very high, excelent, all well explained. Videos vary from 5 to 30 minutes, but the average is between 15-20 minutes (90 and 120 minutes per week). The lectures are good for an introduction course, and at the end, the student will be able to make and create basic operations with R.
THe course is designed to be held in 4 weeks, but I will add an extra one. In my opinion, week 3 lecture is too wide for learning 2 graphical tools, both very complex, and I will divide in two different weeks, also adding basic exercises. In my opinion, week 3 is the more complex of this course, and programming skills are welcome.
It is highly recommended to have good programming skills, and, although it was my case, I must admit last weeks cost me an extra effort and more time than I expect. Finally, I pass the course, but … if you think it’s not enought, you can enroll in a new course to go further.
In the forum included in the course, it was criticized that one part of last week was related to regular expressions, something that can be used and applied to many other programming languages. Personally, regular expressions was a topic it never interested me, so, for me it was useful. The second part of week 4 was for classes and method (too complicated, in comparision to other languages, and in my opinion)
To end with, if the course wasn’t enought for you, the next course to enroll is Data Analysis, and you’ll have 8 more weeks to “play” with R.
In my case, I discourage a lot last week of the course, basicaly due to Python: more easy, and for me, the sintax in R seems too complicated, and at work I am more profitable with Python than R. Also, with the statistics Python packages and libraries I can solve the mayority of the problems I need to solve, instead of doing it with R. As an extra point to Python, I can use it for almost everything!
I like coursera.org
I was very surprised about coursera.org: there is a large variety of courses to choose, and the quality of the contents and really good. I’m also taking two new courses!!
So, you should visit coursera.org if you need a place to improve your knowledge!