2 or 3 credits
Fall 2026 Lecture Upper Division
This course is an introduction to the techniques and algorithms for creating effective data visualization. Visualizations are graphical depictions of data that can improve comprehension, communication, and decision making. This course emphasizes application in business settings where visual representation methods that are covered in this course will improve our understanding of complex data and models. We focus in particular on pattern identification, difference and trends in data sets across categories, space, and time. In addition to participating in in-class discussions, students will have sufficient hands-on experience with the tools and techniques covered in this course. Students will be expected to complete several short programming and data analysis assignments. Students will also have an opportunity to work as groups on a final project. Permission of department required.
Learning Outcomes1Understand the key techniques and theory used in visualization, including data models and graphical perception.
2Apply perception and cognition principles in visualization.
3Become familiar with a large number of data visualization tools.
4Transform large database for visual displays using various representation techniques.
5Critique various visualization representation and interaction techniques.
6Read and discuss research papers from the visualization literatures.
Prerequisites
Restrictions
made by Purdue students.