ECS 273: Visual Analytics

ECS 273
Visual Analytics
Effective Term
2023 Winter Quarter
Learning Activities
Lecture: 3 hours
Project (Term Project): 3 hours
Analytical reasoning using visual means, data and visual transformations, exploratory visualization, explanatory visualization, interactive intelligent systems, qualitative and quantitative evaluation.
Graduate standing.
Enrollment Restrictions
Pass One restricted to graduate students in Computer Science only; Pass Two restricted to graduate students only.

Summary of Course Content

Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces. Students will learn and practice how to design, realize, and evaluate visual analytics methods integrating interactive visualization, statistical analysis methods, machine learning, and high-performance computing techniques for solving complex data analysis problems found in real-world applications.

Lectures will cover the following topics:

  1. Introduction to visualization
  2. Visual analytics pipelines
  3. Data cleaning and uncertainty
  4. Interaction techniques
  5. High dimensional data
  6. Network data
  7. Event sequence data
  8. Time series data
  9. Text data
  10. Geospatial data
  11. Collaborative analysis
  12. Visualization and machine learning
  13. Evaluation  

Illustrative Reading
Illuminating the Path: The Research and Development Agenda for Visual Analytics. James J. Thomas and Kristin A. Cook. United States Department of Homeland Security, 2005

Potential Course Overlap
A few subtopics on visualization fundamentals overlap with parts of ECS272.

Course Category