Course Detail
Units:
3.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisites: 'C-' or better in CS 3500 AND (Full Major status in Computer Science OR Computer Engineering OR Software Development)
Description
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.