Dear all, we're excited to introduce our upcoming online course, "Reproducibility Data Analysis with R," taking place from 9-12 October 2023. Course website: [ https://www.physalia-courses.org/courses-workshops/r-reproducibility/ ]( https://www.physalia-courses.org/courses-workshops/r-reproducibility/ ) In this course, you will gain the essential skills to ensure your R projects are not only efficient but also highly reproducible. Learn how to organize your projects for seamless collaboration using tools like RMarkdown, renv, version control, and more. If you've worked with R and want to minimize the pain of sharing and reproducing your work, this course is perfect for you. Basic prior experience with R is recommended. By the end of this course, you'll be equipped to: Create an R project that produces reproducible documents. Manage a reproducible environment, specifying packages and their versions. Effectively track changes using git. Collaborate seamlessly with others on GitHub. Create and publish containers for your projects. Course Schedule: Monday: Introduction to reproducibility, RStudio projects, R markdown. Tuesday: "here" package, Git and GitHub, sharing data. Wednesday: Automate project structure with "rrtools," managing dependencies with "renv." Thursday: Introduction to Containers, Docker, and publishing containers on Dockerhub. Best regards, Carlo --------------------
Carlo Pecoraro, Ph.D Physalia-courses DIRECTOR i...@physalia-courses.org mobile: +49 17645230846 Follow us on [ Twitter ]( https://twitter.com/Physacourses ) & [ Mastodon ]( https://mas.to/@PhysaliaCourses ) [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
