Dear all,
We are pleased to announce our upcoming online course: Reproducibility in Data Analysis with R
 
Dates:  8–11 June 
 
Course website: https://www.physalia-courses.org/courses-workshops/r-reproducibility/ 
 
Reproducibility is a fundamental aspect of good scientific practice, yet in many projects analyses remain difficult to rerun or verify. Missing files, changing software versions, unclear workflows, and poorly documented code often make even our own results hard to reproduce over time.
In this course, we focus on practical solutions to these challenges. The goal is to help participants develop a clear, structured, and reliable workflow for data analysis in R, from the early stages of a project to sharing final results.
 
We will work in a very hands-on way, combining short lectures with live coding and exercises. Participants will learn how to organise projects properly, document their analyses, and manage software dependencies so that results remain stable and reproducible over time.
 
We will also introduce a set of widely used tools that are now standard in many research environments, including Quarto for reproducible reporting, Git and GitHub for version control and collaboration, and renv for managing R environments. In addition, we will show how to structure projects as research compendia, making code, data, and documentation easier to share and reuse.
 
Finally, we will explore how computational environments can be made fully portable using Docker containers, ensuring that analyses can be reproduced across machines and in the future without technical issues.
By the end of the course, participants will have a practical, end-to-end workflow for reproducible research that can be directly applied to their own projects.
 
 
For the full list of our courses and workshops, please visit: https://www.physalia-courses.org/courses-workshops/ 

Carlo Pecoraro, Ph.D
Physalia-courses DIRECTOR
info@physalia-courses.org
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