R for Data Science (Spring 2026)
A 3-day course for researchers with some experience in R and who are looking to level up their data science skillset
The course starts by reinforcing the core R programming structure, including RStudio, R scripts, R projects, and Quarto documents. The focus then shifts to advanced data wrangling using the tidyverse to prepare data for analysis and exploratory data analysis (EDA) with ggplot2 to visualize patterns.
Participants will also learn to perform PCA with ggfortify, automate tasks with R scripting (loops, conditionals, functions), and build basic models such as linear regression, logistic regression, and clustering.
The course concludes with a full project, guiding participants from data preparation and exploration to modeling, while ensuring the work is reproducible and well-documented.
By the end of the course, students will have the skills to manipulate, analyze, and visualize data in R, perform common models, and document their work effectively.
Requirements
There are no prerequisites to participate in the course. Please come prepared for the first day of the course by following the directions provided in advance by course instructors regarding downloading R, R Studio, and several small set up tasks.
Interested?
➡️ If you are an employee, sign up here
➡️ If you are a PhD student, sign up here
Course Disclaimers
- The course is free of charge and intended for all KU researchers, and especially PhD students, at SUND
- A no-show fee will be implemented for registrants who do not attend the course
- If you are a PhD student and you would like to receive ECTS credits for participating in this course, you must enroll through the PhD school system
- If you are not a PhD student and sign up via the PhD school registration link, you will be charged for the course
- Please be advised that course participation via the PhD school happens under the PhD school's terms and conditions which HeaDS has no influence over