Data Visualization


Stanford School of Engineering

Computer Science: Data Visualization


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


Prerequisite: The class is aimed at graduate students and advanced undergraduates. Familiarity with the material in CS147, CS 148 and CS142 can be useful. Even more important is a basic working knowledge of web-programming, especially Javascript and D3. Experience with data analysis applications (e.g. Excel, Matlab, R).

Topics include

  • Exploratory data analysis
  • Perception and interaction
  • Data-drive documents (D3) and their uses
  • Using space effectively
  • Animation, color and graph layout

Course Availability

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 education section.

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