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Welcome to the blog of the Coding & Data Visualization course. The course is designed for postgraduate students in management studies. It aims to provide a modern introduction to data transformation and visualization in R, embracing state-of-the-art programming tools such as generative AI coding assistants.
Instead of focusing on syntax, the course emphasizes the understanding of underlying principles and concepts that are essential for effective data analysis and visualization in R. Technical details are still part of the course, but they are presented as means of highlighting fundamental data science ideas. While the advent of generative AI closes the technological gap between specialized programmers and non-programmers, it simultaneously changes the way we work with code. Less time is spent on writing code, and more time is spent on reviewing and reasoning about code. The course material and the in-class activities strive to reflect this shift in the programming paradigm.
The course emulates the workflow of a data analysis project starting from scratch. Instead of relying on prepared datasets, it raises a question motivated from a contemporary topic, and uses real-world data from Eurostat (Eurostat 2025c, 2025b, 2025a) to learn more about it. The data is collected, cleaned, transformed, combined, and visualized in a series of steps that are typical for a data science project.
In terms of topic presentation, the course follows a top-down approach inspired by (Wickham, Getinkaya-Rundel, and Grolemund 2023). While there is thematic overlap with the book, the symmetric difference of the covered topics is substantial.