Dec 30, 2024  
2019-2020 Undergraduate Academic Catalog 
    
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2019-2020 Undergraduate Academic Catalog [ARCHIVED CATALOG]

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UX 3025 - Data Visualization

3 lecture hours 0 lab hours 3 credits

Course Description
Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns. Data visualization combats information overload and makes data easier to comprehend and understand complex data sets, therein making it to remember and make decisions. Furthermore, visual representations help to engage more diverse audiences in the process of analytic thinking. This form of visual communication is a highly sought-after skill as companies look to hire candidates who can present their insights clearly. Students will learn the fundamentals and best practices of data visualization analysis and take a deep dive into how the mind perceives and interprets visual information with. Data visualization strategies and approaches will be taught through a mixture of lecture, discussion, and the use of data visualization tools (e.g. Tableau). (prereq: UX 1511 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
  • Know how the mind perceives and interprets visual information 
  • Recognize data visualization best practices and know how to model data in a visual manner 
  • Demonstrate knowledge in gathering, preparing, and analyzing complex data sets 
  • Apply knowledge of color, typography, and visual design practices to visualize data 
  • Explain and present the story surrounding data 
  • Show proficiency in basic functions of data visualization software to create infographics, interactive data visualizations, and data maps 

 

Prerequisites by Topic
  • Data research and analysis
Course Topics
  • Introduction to data visualization and visual perception
  • Fundamentals of visualization, data modeling, and compare and contrast
  • Data visualization best practices and not-so-best practices 
  • The use of color in data visualization and dashboard design
  • Typography and data visualization design
  • Infographics, interactive data visualization, and mapping data
  • Owning your data story
  • Data visualization tool
Coordinator
Dr. Nadya Shalamova


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