By Brian Back
Whether you’re plotting a simple time series or building a predictive model for the next election, the R programming language’s flexibility will ensure you have all the capabilities you need to get the job done. In this blog we will take a look at five effective tactics for learning this essential data science language, as well as some of the top resources associated with each. These tactics should be used to complement one another on your path to mastering the world’s most powerful statistical language!
1. Watch Instructive Videos
We often flock to YouTube when we want to learn how to play a song on the piano, change a tire, or chop an onion, but why should it be any different when learning how to perform calculations using the most popular statistical programming language? LearnR, Google Developers, and MarinStatsLectures are all fantastic YouTube channels with playlists specifically dedicated to the R language.
2. Read Blogs
There’s a good chance you came across this article through the R-bloggers website, which curates content from some of the best blogs about R that can be found on the web today. Since there are 750+ blogs that are curated on R-bloggers alone, you shouldn’t have a problem finding an article on the exact topic or use case you’re interested in!
A few notable R blogs:
3. Take an Online Course
As we’ve mentioned in previous blogs, there are a great number of online classes you can take to learn specific technical skills. In many instances, these courses are free, or very affordable, with some offering discounts to college students. Why spend thousands of dollars on a university course, when you can get as good, if not better (IMHO), of an understanding online.
Some sites that offer great R courses include:
4. Read Books
Many times, books are given a bad rap since most programming concepts can be found online, for free. Sure, if you are going to use the book just as a reference, you’d probably be better off saving that money and taking to Google search. However, if you’re a beginner, or someone who wants to learn the fundamentals, working through an entire book at the foundational level will provide a high degree of understanding.
There is a fantastic list of the best books for R at Data Science Central.
You can read articles and watch videos all day long, but if you never try it for yourself, you’ll never learn! Datazar is a great place for you to jump right in and experiment with what you’ve learned. You can immediately start by opening the R console or creating a notebook in our cloud-based environment. If you get stuck, you can consult with other users and even work with scripts that have been opened up by others!
I hope you found this helpful and as always if you would like to share any additional resources, feel free to drop them in the comments below!
Resources Included in this Article
- LearnR: https://www.youtube.com/user/TheLearnR/featured
- Google Developers: https://www.youtube.com/playlist?list=PLOU2XLYxmsIK9qQfztXeybpHvru-TrqAP
- Marin Stats Lectures: https://www.youtube.com/user/marinstatlectures
- Revolutions: http://blog.revolutionanalytics.com/
- R-bloggers: https://www.r-bloggers.com/
- Civil Statistician: http://civilstat.com/
- Flowing Data: http://flowingdata.com/
- Datazar: https://www.datazar.com/
- Udemy: https://www.udemy.com/courses/search/?q=r%20language&src=sac&kw=r%20languag
- Data Camp: https://www.datacamp.com/
- Coursera: https://www.coursera.org/learn/r-programming
- lynda.com: https://www.lynda.com/R-training-tutorials/1570-0.html
- Data Science Central: http://www.datasciencecentral.com/profiles/blogs/10-great-books-about-r-1
R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more…
Source:: R News