Packages

swirl Interactive introduction to R so you can learn R, using R.
tidyverse Core package to load packages dedicated to working with tidy data frames.

Resources

RStudio Cheat Sheets great visual maps for data analysis (highly recommend the dplyr, data import, and ggplot2 sheets!)
R style guide to make sure your code is beautiful because when your code is easy to read, your future self will thank you.
UNL Statistics Help Desk Statistical Cross-disciplinary Collaboration and Consulting Lab (SC3L)
CRAN task views Grouping notable packages in specific topics such as Phylogenetics, Time Series, Experimental Design, etc.
Happy Git and GitHub for the useR a long-form tutorial on working reproducibly in R and RStudio with Git and GitHub
Sampling, Data Management and Visualization UNL Course lead by Dr. Drew Tyre

Twitter is a great resource for getting help in R. You can browse the #rstats hashtag to see what’s going on.

These accounts are great to follow to see what’s going on in R

@RLangTip tweets out useful tips and tricks to use R
@dataandme aka Mara Averick often tweets out links to useful tutorials in R
@juliasilge data scientist at StackOverflow
@_inundata aka Karthik Ram, a data scientist at the Berkeley Institute for Data Science
@JennyBryan currently works at RStudio and very concerned with usability
@hadleywickham creator of the tidyverse and cheif data scientist at RStudio

Upgrading R on Windows can sometimes be frustrating. The intstallr R package helps with this process.