This is the course website for Data Visualization, instructed by Jill Naiman (jnaiman@illinois.edu).
Below, you will find the materials for each week, as well as the syllabus that includes contact information and a course outline.
Lecture 1 - Class Introduction & Why we Visualize
The syllabus for the course, along with discussions about "what" visualizations are, and how to orient yourself in the course.
What are some of the basics of how we interpret visualizations? How can we describe the process of making choices, understanding our audience, and so forth?
Lecture 2 - Data storage & Operations, Image data
When we draw something on a screen, how do we represent that internally, and how is that translated into pixels? How are values transformed from 0's and 1's into values we can manipulate and understand?
How to submit homework with the TurnItIn framework
More examples of drawing images in 2D; binary representations
Lecture 3 - Colors and Color maps, Types of viz
How do colors work? What are the different ways we can map colors to values? What should we keep in mind when doing this?
Lecture 4 - Widgets & Traitlets for Interactivity
We talk about the basics of using Traitlets and data binding in visualization.
Lecture 5 - Grammar of Graphics & bqplot
We introduce the basics of bqplot & how it relates to grammar of graphics
Linking data a bit about maps (if we have time)
Lecture 8 - Choosing viz & Online viz platforms
Choosing what viz type to use, and an introduction to Vega/Vega-lite and Starboard
Lecture 9 - Viz audience, Final Project Info
Considerations of audience, review about final projects, more with vega lite & Starboard, Jekyll
Lecture 10 - Starboard, Publishing & more in Jekyll
Publishing your viz, vega-lite with Altair in a Jekyll page
Lecture 10 extras - more with Vega-lite
More with vega-lite
Lecture 11 - Publishing & Validation
More about publishing and validation, and Jekyll+vega-lite+Altair
Lecture 12 - 3D graphics, Intro to SciViz
How your computer and the internet process 3D graphics. What is scientific visualization?
Lecture 13 - Scientific Visualization, notes on final project
More about scientific visualization
Lecture 15 - WordClouds, networks, and final project
How to analyze text data, viz of networks, and where to go from here.
