A model for a data visualization and exploration course

Abstract

In response to a large backlog of demand for data analytics expertise, universities are adding analytics courses and/or programs. Data visualization and exploration are among the pillars of the analytics curriculum and should be included in analytics programs. This article presents the philosophy, structure, and content of a data visualization and exploration course for senior undergraduate and master's level students. It presents the learning objectives, detailed criteria for selecting the reading materials, and visualization software for this course. In addition, this article shares lists of required and optional articles that were selected by an extensive review of literature in the field of data visualization and exploration. Analysis of assessments by the instructor and the independent assessment of student capstone projects by two reviewers showed that students learned the materials well and properly applied the knowledge they gained in this course to completing the capstone project. Student comments indicate that the course was well designed, that they enjoyed the course content, and that they found working with the visualization software beneficial.