Resources for R programming language

"Software Carpentry workshops are hands-on, two-day events that cover the core computational research skills needed to be productive as an individual scientist or in small research teams. No previous experience is needed and each workshop is taught by experienced researchers who use these tools in their own work. Participants will learn how to automate tasks using the Unix shell, will be introduced to a structured programming language like Python or R, and will gain experience using Git and Github for version control."

A series of workshops created by LATIS (Liberal Arts Technology and Innovation Services) that are free and open to all faculty and graduate students

A monthly event where experienced staff from the libraries, Liberal Arts Technology and Innovation Services, and Research Computing will connect attendees with an expert for 30 minutes of hands on help. Advance sign-up is required.

We are the University of Minnesota affiliate of Hacker Hours providing free office hours for coders, developers, looking to learn new skills, or anyone who wants to learn to code. Want to learn? Want to mentor? Come to our next meeting!

Workshops include preforming linear regression with R and Introduction to reproducible data with R.

Hosted by the Morrell Lab, Does[0]compute? (pronounced “Does naught compute?”), is intended to foster a discussion about best practices in computational biology

Author: Garrett Grolemund
Creative commons licensed text written with non programmers in mind. "This book will teach you how to program in R with hands-on examples"

Authors: Garrett Grolemund and Hadely Wickham
Creative commons licensed text. "This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it"

Introductory lessons on distant reading for academics, including lessons on Stylometry with Python, Basic Text Processing with R, and Getting started with Topic Modeling and Mallet.

OpenRefine (formerly Google Refine) is a powerful tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data.

LinkedIn Learning has high-quality, online training videos for all skill levels including software, technologies (3D Animation, Audio, Photography), design, and business topics. Learning paths can be a great way to explore a topic and develop skills. Suggested learning paths for R include master R for data science and advance your skills as an R expert

This resource is not paid by the Libraries, but is accessible by all current students, faculty and staff of the University of Minnesota system. For more information please visit OITs information page.

Where you can download R and find documentation

An open source development environment for working with R