This course is an introduction to the field of Data Visualization. Students will learn the fundamentals of data visualization. We will study different visualization methods and discuss how they can be used to visualize and explore quantitative datasets effectively. We will evaluate several approaches and learn how human perception interprets visualized data in various different ways.

PLEASE NOTE THAT THE INFORMATION ABOUT THE TEACHING AND ASSESSMENT METHOD(S) USED IN THIS COURSE IS WITH RESERVATION. A RE-EMERGENCE OF THE CORONAVIRUS AND NEW COUNTERMEASURES BY THE DUTCH GOVERNMENT MIGHT FORCE COORDINATORS TO CHANGE THE TEACHING AND ASSESSMENT METHODS USED. THE MOST UP-TO-DATE INFORMATION ABOUT THE TEACHING/ASSESSMENT METHOD(S) WILL BE AVAILABLE IN THE COURSE SYLLABUS.

Over the last decades organizations have started to accumulate enormous amounts of data both through their internal information systems as well as from external sources such as sensors or external vendors. While this data is partly used to support algorithmic and automized decision-making, many tasks still require a human in the decision-making process. For these types of processes, it often becomes necessary to present complex, multidimensional datasets in a way that supports knowledge discovery or understanding. To do so efficiently and effectively, visualization designers need to have a fundamental understanding of the principles governing human visual perception as well as how to translate these principles into best practices. In this course students will develop both, academic skills related to the systematic and scientific design of visualizations as well as practical knowledge on how to implement these theoretical skills using the Tableau Desktop Software Package.

Textbook, Academic Articles

There are no formal prerequisites.