There are always new things to learn in R and possibly you'll pick up on ways to do things better than we did in the class.

R's user base is large, loyal and (mostly) caring. When you get stuck on something, you'll most likely be able to find the answer online.

But before endlessly browsing Google or getting trolled on the forums (more on that later), I'd suggest you read a couple books:

R for Excel Users by John Taveras. This is my favorite introductory book in R. It's great regardless of whether you've used Excel.

This will take you beyond the concepts covered in our seminar without overwhelming you.

R for Data Science by Hadley Wickham and Garrett Grolemund.

This is an intermediate-level book on R from the creators of the tidyverse. This is likely overdoing it for a beginner.

If you're interested in data science, keep working on R and picking this book up every so often until you feel comfortable with it.

Getting an error code? Google it and the majority of the time you will find an answer and explanation that will solve it.

How to use StackOverflow

StackOverflow is a great resource but be considerate before posting your own questions. Those responding can resemble the famous Seinfeld Soup Nazi if you have not done a lot of preparation and your own work before asking a question.

Also, subscribe to R bloggers at http://www.r-bloggers.com.

This is a daily roundup of the best R blogging.

While many of the posts are rather advanced, if you see a post that interests you, take a few minutes and at least skim it and get a sense of what packages and techniques the author is using.

The important thing is to keep learning about R and to be be creative in thinking about how it can help you.

I hope this training session has helped you.

Please email me at george@georgejmount.com with questions, comments or suggestions.