Data Visualization and Interpretation. 3 credits, 3 contact hours

Catalog description

The course will focus on training students with the knowledge of data visualization theory, techniques, and tools. Students will learn why and how visualization can be applied in the human-centered data science pipeline and the different uses of visualization, such as in exploratory data analysis, and in the communication of data-driven insights. They will gain practical experience in interpreting, critiquing, and comparing visualization techniques by using real-world data sets and case studies. Students will also develop interactive visualization interfaces as part of the class project. They will gain a broad understanding of how visualization can enhance trust and interpretation of machine learning models. The students will read and learn about recent progress in the areas of information visualization, visual analytics, and human-data interaction.