Introduction to Data Visualization | Courses | Institute of Design

In 2026, after nearly 90 years, the Institute of Design was folded into Illinois Tech's School of Design & Society.
This website is an archive of the impactful and inspirational work produced by the ID community before that transition.

László Moholy-Nagy opened the New Bauhaus in Chicago in 1937, treating design as a discipline that was teachable, testable, and consequential. Nine decades on, its scope had widened from the things people use to the systems they depend on: hospitals, government agencies, classrooms, supply chains, digital platforms. Along the way, ID community members developed the published research, methods, and frameworks that designers rely on every day.

Chief among them is human-centered design: close attention to how people actually live, and advocacy for what that research reveals. It shaped designers who are comfortable with complexity and ambiguity: curious, rigorous, inclusive, and stubbornly optimistic about design's ability to change the systems that shape our lives.

To every one of them, who taught, studied, built, critiqued, and stayed late in the studio: thank you, and keep designing.

Show archive notice

We use technologies, such as cookies, to customize content and advertising, to provide social media features, and to analyze traffic to the site. By using or registering on any portion of this site, you agree to our privacy and cookie statement.

Privacy Statement

institute
of desiGn

Introduction to Data Visualization

An exploratory and immersive journey of making information understandable and useful.

Objective & Outcomes

This course will take on these interrelated awareness, educational, and communication design challenges while striving to build student skillsets in a wide variety of contemporary design application spaces. Students will complete a variety of data research and visualization challenges throughout the course, explore data aesthetics and persuasion techniques, develop coding skills and data manipulation and research abilities, and complete a self-defined project focused on interactive and journalistic data storytelling.

Typical Schedule

Session 1: Introduction to Data Visualization with Python
Session 2: Data Wrangling for Visualization
Session 3: Advanced Plotting with Matplotlib
Session 4: Interactive Visualization with Plotly
Session 5: Geographic Visualization with Geopandas & Folium
Session 6: Statistical Visualization with Seaborn
Session 7: Final Project