Interactive Lab
Computer Visualization
Explore, interact with, and modify live visualizations for each lecture.
Tweak parameters or edit the code directly to see changes in real time.
Basic Visualization Charts
Core principles of data visualization — why it matters and how different chart types serve different analytical goals.
Data Preprocessing
How missing values, outliers, and rescaling change a dataset — and how to tell whether a preprocessing step actually helped, on the course's own student dataset.
Visual Variables
How color, size, and shape encode information — and how misusing them confuses the viewer instead of helping them.
Color Blindness
How color vision deficiencies affect the perception of data visualizations — and how to design charts that work for everyone.
Dimension Reduction & PCA
Principal Component Analysis — how to compress high-dimensional data into fewer dimensions while keeping most of the information.