Fee may apply
Visual media are increasingly generated, manipulated, and transmitted by computers. When well designed, such displays capitalize on human facilities for processing visual information and improve comprehension, memory, inference, and decision making. Yet the digital tools for transforming data into visualizations still require low-level interaction by skilled human designers. As a result, producing effective visualizations can take hours or days and consume considerable human effort. In this course we will study techniques and algorithms for creating effective visualizations based on principles and techniques from graphic design, visual art, perceptual psychology and cognitive science. The course is targeted both towards students interested in using visualization in their own work as well as students interested in building better visualization tools and systems. In addition to participating in class discussions, students will have to complete several short programming and data analysis assignments as well as a final programming project.
What you will learn
- The purpose of visualization and visualization design
- How to clearly and effectively communicate complex data analysis
- How to create better tools for data visualization systems
- Exploratory data analysis
- Perception and interaction
- Data-drive documents (D3) and their uses
- Using space effectively
- Animation, color and graph layout
Note on Course Availability
This course is typically offered Winter quarter.
The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate certificate homepage.
|Dates:||January 6 - March 13, 2020|
Provides Stanford University credit that may later be applied towards a graduate degree or certificate. Includes access to online course materials and videos for the duration of the academic quarter. Starting Autumn 2016 there is a $100 fee per course for courses dropped before the drop deadline. Click here for more information about our Registration Policies.
NotesEnrollment Dates: October 27 to December 9, 2019
Computer Science Department Requirement
Students taking graduate courses in Computer Science must enroll for the maximum number of units and maintain a B or better in each course in order to continue taking courses under the Non Degree Option.
This course may not currently be available to learners in some states and territories.