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Course on Reproducibility Data Analysis with R

Dear all,
there are only a few seats our upcoming online course, "Reproducibility Data Analysis with R" scheduled for 28-31 October 2024. This course is designed to help you streamline collaboration and maximize the reproducibility of your R projects.
 
Course website: [ https://www.physalia-courses.org/courses-workshops/r-reproducibility/ ]( https://www.physalia-courses.org/courses-workshops/r-reproducibility/ ) 
 
 Have you ever struggled with running your own R code after some time or when sharing it with colleagues? This course will teach you how to organise your projects, manage dependencies, and use tools like RMarkdown/Quarto, renv, Git, and Docker to ensure your code is reproducible and easy to collaborate on.
 
This course is ideal for researchers, data scientists, and anyone using R to generate documents and collaborate with others. Basic experience with R is recommended. If you do not have experience with R, have a look at our course in September: [ https://www.physalia-courses.org/courses-workshops/r-tidyverse/ ]( https://www.physalia-courses.org/courses-workshops/r-tidyverse/ )
 
 
 
By the end of this course, participants will be able to:
Create reproducible R projects.
Manage packages and environments with renv.
Track and collaborate on code with Git and GitHub.
Create and publish containers with Docker.
Program:
Daily Schedule: 9 AM - 12 PM (Berlin time)
Monday: Introduction to reproducibility, RStudio projects, RMarkdown/Quarto.
Tuesday: Git, GitHub, and collaboration.
Wednesday: Managing dependencies and sharing data.
Thursday: Introduction to containers and Docker.
Best regards,
Carlo
 
 
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Carlo Pecoraro, Ph.D


Physalia-courses DIRECTOR

info at physalia-courses.org

mobile: +49 17645230846