NCEAS Learning Hub’s coreR Course

Preface

October 2 - October 6, 2023

Welcome to the coreR Course

A five-day immersion in R programming for environmental data science. Researchers will gain experience with essential data science tools and best practices to increase their capacity as collaborators, reproducible coders, and open scientists. This course is taught both in-person and virtually.

Course Learning Objectives:

  • Effectively manage data using tidy data practices and developing quality metadata
  • Establish best practices and utilize tools like Git & GitHub, and Data Management Plans to optimize your collaboration
  • Better communicate scientific analyses and results using Markdown, GitHub webpages, and R packages like ggplot and leaflet
  • Increase your familiarity and confidence with data science tools

Schedule

Code of Conduct

By participating in this activity you agree to abide by the NCEAS Code of Conduct.

About this book

These written materials are the result of a continuous and collaborative effort at NCEAS to help researchers make their work more transparent and reproducible. This work began in the early 2000’s, and reflects the expertise and diligence of many, many individuals. The primary authors are listed in the citation below, with additional contributors recognized for their role in developing previous iterations of these or similar materials.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Citation: Halina Do-Linh and Camila Vargas Poulsen (2023). coreR Course. NCEAS Learning Hub. URL learning.nceas.ucsb.edu/2023-10-coreR.

Additional contributors: Ben Bolker, Amber E. Budden, Julien Brun, Samantha Csik, Natasha Haycock-Chavez, S. Jeanette Clark, Julie Lowndes, Stephanie Hampton, Matthew B. Jones, Samanta Katz, Erin McLean, Bryce Mecum, Deanna Pennington, Karthik Ram, Jim Regetz, Tracy Teal, Daphne Virlar-Knight, Leah Wasser.

This is a Quarto book. To learn more about Quarto books visit https://quarto.org/docs/books.