Online course: Data Analysis with R

R is a language that has become one of the most popular tools for manipulating, visualizing and analyzing data. While there are many R courses, learning these skills can involve a steep learning curve, especially for people with no experience in programming or data analysis. This two-day remote course (delivered via Zoom) aims to help with this initial difficulty by equipping learners with essential skills in using R, including data wrangling and plotting.

The course topics include data importing and exporting, handling real-life data sets and creating publication-ready plots with R. The topics will be covered using both hands-on teaching and independent exercises.

Learning outcomes

After attending this course, participants will be able to:

  • Navigate RStudio
  • Understand R syntax and how to write R code
  • Import and export data using R
  • Use tidyverse for data wrangling
  • Use ggplot2 for creating high-quality plots

Before the course

You need a Haka account to access the course environment. If you do not have one, please contact us ( as soon as possible after registering. You do not have to install R on your own computer, as the course will run on an R environment available on the CSC Notebooks service. Instructions for logging into Notebooks using your Haka login details will be supplied in advance (please also make sure that you are able to log in before the course).”

While no previous background in programming is expected and there is no requirement to complete exercises prior to the course, links to the teaching materials will also be provided to participants in advance.


No prior experience of programming or using R is expected
No data analysis or statistical experience is required
A Haka account is required to access CSC Notebooks.


Day 1

09:00 – 14:30
Hands-on teaching via Zoom
Basic features of R
Starting with data
Data manipulation (introduction)

14:30 onward
Independent exercises:
Data manipulation (continued)

Day 2

09:00 – 14:30
Hands-on teaching via Zoom
Feedback and solutions to independent exercises
Data visualization (introduction)

14:30 onward
Independent exercises
Data visualization (continued)


10:30 – 10:45 (short coffee break)
12:00 – 13:00 (lunch break)