Instructor |
Dr. Loretta Y.K. Choi
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Teaching assistants |
Mr. Nenglun Chen
Mr. Cheng Lin
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Syllabus |
This course introduces the basic principles and techniques in visualization
and visual analytics, and their applications. Topics include human visual
perception; color; visualization techniques for spatial, geospatial and
multivariate data, graphs and networks; text and document visualization;
scientific visualization; interaction and visual analysis. |
Introduction by Instructor |
Data and information visualization concerns about the representation of
abstract data in intuitive visual forms, with visual analytics further
focuses on the use of interactive visual interface to facilitate analytical
reasoning that supports the visual information cognition and decision-making
process. In this course, students will learn the basic knowledge in
visualization and visual analytics. There will be lab sessions to provide
students with hands-on experience with data visualization tools. Students
will also be able to apply the techniques they learned from the course in a
group project for data visualization. |
Learning Outcomes |
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Pre-requisites |
Students should have basic programming knowledge, e.g. C++ or Java. |
Compatibility |
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Topics covered |
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Assessment |
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Course materials |
Lecture Notes & Lab Instructions:
- Available from the Moodle course web page
Recommended readings
- Matthew Ward, Georges Grinstein, and Daniel Keim,
"Interactive Data Visualization: Foundations, Techniques,
and Applications", A. K. Peters, Ltd.
- Illuminating the Path edited by J. Thomas and K. Cook,
IEEE Press, 2006, available from
http://nvac.pnl.gov/agenda.stm
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Session dates |
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Add/drop |
15 January, 2018 - 3 February, 2018 |
Quota |
100 |