RaukR 2026 - Summer School - Data Science with R
Description
Join us this August in the beautiful and historic town of Visby and sharpen your R skills with like-minded enthusiasts! As the use of R continues to flourish within the realms of Life Science and Bioinformatics – revolutionizing data transformation, statistical analysis, and the creation of visuals ready for publication – we are thrilled to offer a workshop dedicated to elevating your expertise with R. The course is aimed at both Ph.D. students and researchers within Life Sciences who are already using R for basic bioinformatics analyses and who would like to start using R at a more advanced level.
We are excited to announce our invited guest instructors for this year: Jennifer Bryan (Posit), and more guest speakers to come.
Please consider joining us for this enriching experience. We’d also greatly appreciate you sharing this opportunity with others who might be interested.
For more complete information please visit the website!
Content Providers
Learning Outcomes
We will be covering a number of topics in R programming with focus on R features helpful in data analyses workflow. These typically include:
R code style guide & best practices
Code debugging, optimization and profiling
Parallelization and vectorization in R
Crafting your own functions
Generating reports, presentations and websites with Quarto
Coding in Positron
R and AI, from code completions to agents
Object oriented programming and R classes: S3, S4, R6 etc
Anatomy of an R package: Creating your own package from scratch
Tidy data analysis using tidyverse
Data visualization in R
Developing web applications using Shiny
Collaborative work using Git and GitHub
Team project work - developing data analyses workflow in R using acquired skills
Note that the exact topics covered may vary slightly from year to year based on participant feedback, instructors and emerging trends in R programming.
Prerequisites & Technical Requirements
Prerequisites
In order for you and other participants to benefit the most, you should consider yourself eligible if you are comfortable with:
Reading, writing and transforming data
Installing and using third-party packages
Plotting using base and/or ggplot2
Understanding of R data types (strings, vectors, data.frames, lists etc.)
Writing functions and using control structures (if, for, while)
Basic understanding of RMarkdown and/or Quarto
Technical requirements
A laptop, preferably with admin access.
Topics & Tags
Affiliations & Networks
Activity log
