Archived course site for the Spring 2026 offering. Below you will find the structure, policies, and weekly schedule as they were for that term.

• Understanding Visual Analytics Principles: Gain a foundational knowledge of visual analytics, including analytical reasoning techniques, data representation and transformation, and visual representation and interaction techniques.
• Practical Application of Visualization Tools: Develop proficiency in using various visualization tools and coding assignments to analyze and interpret complex data sets.
• Critical Analysis of Visualizations: Enhance skills in critically evaluating visualizations, identifying effective design elements, and recognizing potential misrepresentations.
• Collaborative Project Development: Experience working in pairs to create a comprehensive visualization project, from conception to presentation, fostering teamwork and project management skills.
• Effective Communication of Data Insights: Learn to present data-driven insights clearly and persuasively through written reports and oral presentations.

Through hands-on experience and project work, you will also gain more experience in:

• HTML Fundamentals: Semantic HTML5 elements, document structure, SVG.
• CSS & Styling: Learn modern CSS techniques including Flexbox, Grid, and responsive design principles to create visually appealing visualizations.
• JavaScript Programming: Develop experience JavaScript fundamentals including DOM manipulation, event handling.
• D3.js Data Visualization: Create custom interactive visualizations using D3.js, including data binding, scales, axes, transitions, and event handling.
• Vega-Lite: Build declarative visualizations using Vega-Lite's grammar of graphics, including data transformations and interactive specifications.
• Web Development Workflow: Create a final live web-based project to show off your interactive data visualization skills.

The course is part lecture, and part lab. You will need access to a computer, and install some coding tools. We will work with you to figure out coding assignments, and teach you the basics in the labs.

There are several assignments that you will submit through Canvas. Some assignments require coding, some are design based, and most (hopefully) are fun. You will receive information about each assignment as the course moves on.

There will be one midterm exam (quiz) that will be held in class, and will involve critically analyzing a set of visualizations (more details will be discussed in class).

There will be a final project where you will work in pairs to create a visualization, present it to the class, and write something interesting about it. (more details will be shared)

Note: For due dates and details, refer to the syllabus table below (as of the end of the Spring 2026 term).

This course and the content was heavily inspired by slides from Professor Lyn Bartram (SIAT), and Professor Emily Wall (Emory University). There were also content used from work by Steven Franconeri and Jessica Hullman from (Northwestern University).