Introductory course on design principles and applications of data visualization. This course teaches best practices for visualizing datasets from diverse domains intended to help people make sense of data.
Data visualization is a rich research area that focuses on the design, development, and use of visual representations and interaction techniques to help people understand, explore, and analyze data. In this course, students will
-
Learn fundamental principles of effective data visualization.
-
Understand the wide variety of data visualization techniques and know what visualizations are appropriate for various types of data and for different goals.
-
Understand how to design and implement data visualizations using commercial and open-source software tools.
-
Know how data visualization uses dynamic interaction methods to help users explore, analyze, and make sense of data.
-
Gain an understanding of human perceptual and cognitive capabilities to the design of effective data visualizations.
-
Develop skills in critiquing different data visualization techniques in the context of user goals and objectives.
Students from a variety of disciplines are invited to take the class, as no prior experience with computer programming is expected. The course will involve using data visualization systems as opposed to coding visualizations from scratch. Students from business, science, engineering, and the arts are all welcome.
Course Format
The course will follow a general lecture/seminar style with discussions, viewing of videos, and demonstrations of and hands-on experience with visualization software. While many classes will include interactive exercises, a few specific days may wholly consist of interactive design exercises.
Grading
Grading will be based on exercises, homework assignments, and two quizzes. The weight of each assignment can be found on the assignments page.
Assignments
|
Grades will be determined by a combination of HW assignments, a visualization design project, and two exams.
Summary of weight for course assignments:
|
Component
|
|
Weight
|
|
HW Assignments
|
|
40%
|
|
Design project
|
|
40%
|
|
Exams
|
|
20%
|
Class Participation
It is expected that students will attend class, be prepared by doing the readings, and will pay attention and participate in discussions. We will have a number of interactive exercises during classes where students will turn in their work.
Homework Assignments
TBD
Grading:
Each HW will be graded out of 10 points. Weights toward the final grade are listed above. For each calendar day late, that is 24 hours after the regular due date/time, 10% of the total grade (i.e., one point) will be deducted from an assignment's score. A HW can be turned in up to a week late unless otherwise notified. All the HW assignment details can be found in Canvas.
Project
Description - Capstone design project
Academic Integrity
All students in class are expected to follow Georgia Tech's principles of academic honor and integrity. Details about GT's policies can be found at the OSI web pages and more about our class policies on the class home page. Unless otherwise noted, all work should be strictly your own. If you have any questions about these policies, just ask your instructor.
|
|