In the practical course students will learn how to apply the theoretical concepts and foundations of visual analytics, visual data science, and visualization that have been introduced in the lecture.
Subject
This practical course will cover all steps of the knowledge discovery pipeline, going from data wrangling and preprocessing all the way to interactive data exploration.
Criteria for evaluation
Individual and group assignments.
Methods
Tutorials on various technologies, including Python, Matplotlib, Altair, VEGA, plot.ly and Tableau.
Presentation and discussion of assignments
Language
English
Study material
Will be provided during the semester in the form of hands-on tutorials and exercises.
