A curated repository of university courses, workshops, and online materials for learning and teaching R programming and data science.
rstats-ed is a curated collection of educational resources for learning and teaching the R programming language. It compiles university courses, workshops, MOOCs, and tutorials from various disciplines to help educators and students find quality materials. The project addresses the challenge of discovering structured R courses across different institutions and formats.
Educators designing R-based curricula, students seeking courses, and self-learners looking for structured learning paths in R and data science.
It provides a centralized, community-maintained directory of R courses, saving time for those searching for educational materials. Unlike generic learning platforms, it focuses specifically on R and includes academic courses with syllabi and resources.
List of courses teaching R
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Aggregates courses from various disciplines like psychology, ecology, and social sciences, and includes global offerings in multiple languages, as seen in listings from Brazil to the UK.
Features semester-long university courses with detailed syllabi and resources, such as those from Duke University and Stanford, providing solid foundational learning paths.
Many courses integrate Git, R Markdown, and project management, promoting best practices in reproducible research, highlighted in courses like ESPM 288 at UC Berkeley.
Focuses on modern R data science workflows using the tidyverse, with examples from University of Edinburgh and other institutions teaching data wrangling and visualization.
Relies on community pull requests, so listings can become stale; many courses are from 2017-2020 and may not reflect current R versions or practices.
As a user-submitted directory, there's no vetting process for course quality or accuracy, risking inclusion of outdated or poorly maintained resources.
The directory only lists external resources without built-in tutorials or exercises, so users must navigate to other platforms for hands-on practice.