Dear all
Are you ready to make your R data analysis fully reproducible and collaborative? Join us for our upcoming online course: Reproducibility Data Analysis with R, from 28-31 October !
Why Should You Attend?
Have you ever struggled to get your R code running smoothly on a colleague’s machine or even your own after some time? This course is designed to help you avoid those headaches. You’ll learn how to organize projects for seamless collaboration and reproducibility using powerful tools in the R ecosystem, such as RMarkdown/Quarto, renv, and more.
Course Highlights:
- Create Reproducible R Projects: Learn to produce documents that anyone can run without issues.
- Manage Dependencies: Ensure your code works by specifying exact package versions.
- Version Control: Master git and GitHub for tracking changes and collaborating.
- Containerization: Publish your reproducible environment with Docker.
Who Should Join?
This course is perfect for researchers, data scientists, and anyone who uses R to generate reports and wants to ensure their work is reproducible and collaborative. Basic experience with R is recommended—you should be comfortable reading data and generating basic visualizations.
What You’ll Learn:
- Organize projects to maximize reproducibility
- Manage packages and environments with renv
- Use git for version control and GitHub for collaboration
- Create and publish Docker containers
Daily Schedule (Berlin Time):
- 9 AM - 1 PM: Live lectures, coding sessions, and exercises
- Asynchronous Support: Get help via Slack throughout the course
Detailed Program:
Monday:
- Introduction to Reproducibility
- RStudio Projects: Folder and Package Structure
- RMarkdown: Syntax, Templates, and LaTeX
Tuesday:
- here Package
- Git and GitHub: Setup, Workflow, Collaboration, Documentation
Wednesday:
- Managing Dependencies with renv
- Sharing Data: Repositories, DOI, and Access
Thursday:
- Introduction to Containers
- Docker: Creating and Publishing Containers with Dockerhub
Register Here: https://www.physalia-courses.org/courses-workshops/r-reproducibility/
