Course Detail
Course Components:
Enrollment Information
Enrollment Requirement:
Prerequisites: "C-" or better in CS 3500 AND (Full Major status in Computer Science OR Computer Engineering).
This course  introduces the principles, methods, and techniques for effective visual  analysis of data as applied to data science. We will explore aspects of  visualization related to tabular (high-dimensional) data, graphs, text,  and maps. The course begins by bootstrapping the necessary technical skills (web development with HTML5  and JavaScript), followed by an overview of principles from perception  and design, continues with visualization fundamentals such as  interactions and views, and then focuses on visualization techniques and  methods for non-spatial data types and maps. Throughout the course, we  will continue to analyze, critique, and redesign visualizations.  Students  will acquire hands-on experience designing and implementing  interactive, web-based visualizations using cutting edge visualization  libraries.  A  complementary course - Visualization for Scientific Data - that focuses  on the visualization of spatial data (e.g., grid-based data from  simulations and scanning devices) is offered in the spring.