How to learn R - samedwardes.com

As a data scientist one of the most common questions I get from colleagues and clients is how to get started on learning R. There is a plethora of great options out there today. Some of which are paid, and some of which are free.

TL/DR

The best ways to learn R are:

Coursera Data Science Specialization (John Hopkins University)
R for Data Science by Hadley Wickham and Garret Grolemund
Advanced R by Hadley Wickham and Garret Grolemund
Mastering Shiny by Hadley Wickham
R Packages by Hadley Wickham

My top recommendation - Coursera Data Science Specialization

My number one recommendation is the Coursera Data Science Specialization (John Hopkins University) course. This course will leave you with a solid foundation in base R, the Tidyverse, the concept of tidy data, and concept of reproducibility, and many common data science algorithms.

jhu

Pros:

Suitable for everyone. There is very little prerequisite knowledge required.
Free and paid options (paid options provides a certificate upon completion). If you are able to afford the cost I would recommend opting for the paid version of the course. It is a good way to support the content creators, and personally I find it more motivating to completes the course when I have some “skin in the game”.
Engaging and interesting instructors.

Cons:

The course was created several years ago. I cannot find the exact date, but the R eco system is growing rapidly and constantly changing. Some topics may be slightly out of date.
Big time commitment (estimated time is 11 months, for me it took about 10 months).

Other useful resources

R for Data Science - by Hadley Wickham and Garret Grolemund

If you enjoy reading to learn, R for Data Science by Hadley Wickham and Garret Grolemund is a great way to learn R and basic data science concepts. The book is hosted online for free at https://r4ds.had.co.nz/index.html. You can read the book from front to back, or if if you just need to reference a specific topic the chapters can also serve as stand alone reference. Topics include:

Functions.
The Tidyverse.
Tidy data.
And many more topics!

Advanced R - by Hadley Wickham

Maybe you already consider yourself competent at R and want to take your skills to the next level. Advanced R by Hadley Wickham is a great resource to take your skills to the next level. The book is hosted online for free at https://adv-r.hadley.nz/. The book covers more advanced topics including:

Object-orientated programming in R.
Metaprogramming.
Performance.
And many more topics!

Mastering Shiny - by Hadley Wickham

If your primary focus for learning R is to build Shiny Apps, or it is a skill you want to improve Mastering Shiny by Hadley Wickham is a great place to start. The book is hosted online for free at https://mastering-shiny.org/. Some of the topics covered include:

Designing a user interface (UI).
Reactivity.
Theming your Shiny app.
And more!

R Packages - by Hadley Wickham

I think a theme is starting to develop… Hadley Wickham is awesome. The next book on my list is also authored by Hadley Wickham. R Packages is written for persons how have experience using R. If you want to develop an R package this book is an invaluable resource that I have referenced many times. Whether you are looking to share your packages to the world on CRAN, publish an an internal package for work, or just publish your package on GitHub this book has important information and best practices you should read. The book is hosted online for free at https://r-pkgs.org/index.html. Some of the topics covered include:

How to organize your project.
How to release a package.
A detailed example of how to publish a toy package from start to finish (see Chapter 2: The whole game).

I have no relation to any of my recommendations. They are solely based on my personal experience.