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Introduction to Reproducible and Collaborative Research Practices with R

Introduction to Reproducible and Collaborative Research Practices with R In-Person

Get a jump on learning R at DataLab's 3-day pre-fall Introduction to Research Computing series covering basic coding skills and best practices for reproducible and collaborative research at UC Davis DataLab on September 20-22, 2023 (9 AM - 5 PM).


Dates & Times:
9:00am - 5:00pm, Wednesday, September 20, 2023
9:00am - 5:00pm, Thursday, September 21, 2023
9:00am - 5:00pm, Friday, September 22, 2023
Time Zone:
Pacific Time - US & Canada (change)
DataLab Classroom (Shields Library room 360) (Map )
Davis Campus
  DataLab Workshop  
Registration has closed. (This event has to be booked as part of a series)

This three day workshop series provides an introduction to coding, with an emphasis on leveraging open source tools to develop workflows for collaborative and reproducible reserach. The goal of this series is to increase research integrity via exposure to basic command line tools and version control (git), collaborative cloud tools (GitHub), programming (R), and data and software management best practices. Completion of all sessions and corresponding assessments is required to obtain badges for the UC Davis GradPathways Research Computing micro-credential.

This series is scheduled for in person participation only and seats are limited. Materials build across the sessions and participation on all dates is required. All UC Davis graduate students, postdocs, and faculty with little to no prior programming experience are eligible to apply. Undergraduates engaging in independent and honors research may also apply. Interested non-UC Davis affiliates should reach out to datalab-training@ucdavis.edu.

This intensive series includes sessions on:

  • Reproducibility best practices
  • Unix Command Line
  • Version Control with Git
  • Reproducible Research for Teams with GitHub
  • R Programming Basics (4 modules)

By the end of this series, learners will be able to:

  • Describe tidy data, project organization and programming best practices;
  • Explain the directory structure of their computers and use command line tools to create, copy, edit and delete files;
  • Create new repositories and begin using Git for version control of their individual projects;
  • Push local changes to a repository on GitHub, open and merge pull requests, and create issues for project management;
  • Load tabular data sets into R, compute simple summaries and visualizations, do common data-tidying tasks;
  • Identify where to go to learn more

Can't make it to this training? Check out upcoming workshop schedule. Recordings of prior similar workshops are also available in DataLab's training archive.


This introductory series is intended for academic researchers and does not require prior programming experience. Participants will need to bring a lapop on which they can install software and access the UC Davis wireless network (eduroam).


In advance of the first session install the R, RStudio, and Git software onto your laptop. If you are using Windows, you will need to install additional software. Instructions can be found in DataLab's installation guide. Need help with the installation? Register to attend one of our weekly office hours.

Event Organizer

Profile photo of Pamela Reynolds
Pamela Reynolds

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