From CS294-10 Visualization Sp11
Visual media are increasingly generated, manipulated, and transmitted by computers. When well designed, such displays capitalize on human facilities for processing visual information and thereby 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. The class will meet twice a week. 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. Students will be expected to write up the results of the project in the form of a conference paper submission.
There are no prerequisites for the class and the class is open to graduate students as well as advanced undergraduates. However, a basic working knowledge of, or willingness to learn, a graphics API (e.g. GDI+, OpenGL, Java2D, Flash/Flex) and applications (e.g. Excel, Matlab) will be useful. The final project can be developed using any suitable language or application. While these APIs, applications and languages will not be taught in class, many introductory tutorials at the level required for the class are available on the web. Send me (Maneesh) email if you are worried about whether you have the background for the course.
- Check out the Visualization Gallery and add any interesting visualizations you find on that page.
- Once you create a new account, add yourself to the list of Participants
- Assigned: Assignment 1 (due Jan 26 by 9am)
- Due (by 9am): Assignment 1
Jan 31: No class
- Assigned: Assignment 2 (due Feb 14 before class)
Feb 21: President's Day - No Lecture
- Due: Final Project (project proposal)
Mar 21: Spring Break
Mar 23: Spring Break
May 3: Final Presentations
Course Numbers: CS294-10
Instructor: Maneesh Agrawala (maneesh at cs.berkeley.edu)
Meeting: 405 Soda Hall, Mon-Wed 1-2:30pm
- Maneesh: 635 Soda Hall, MW: 2:30-3pm and by appointment
- The Visual Display of Quantitative Information (2nd Edition). E. Tufte. Graphics Press, 2001.
- Envisioning Information, E. Tufte. Graphics Press, 1990.
Your best bet is to order them online.
Please order soon. Readings will be assigned in the first week of class.
Class participation (10%)
Final Project (40%)
Late Policy: For assignments we will deduct 10% for each day (including weekends) the assignment is late.
Plagiarism Policy: Assignments should consist primarily of your original work, building off of others' work--including 3rd party libraries, public source code examples, and design ideas--is acceptable and in most cases encouraged. However, failure to cite such sources will result in score deductions proportional to the severity of the oversight.
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Tableau's data visualization software is provided through the Tableau for Teaching program.