Data Visualization (CS627) [NIU]

Course Description

Introduction to the study of data visualization with a focus on computer-based design approaches and techniques for manipulating and visualizing data. A variety of data sources and corresponding visualization techniques will be examined covering scientific, social science, financial, and medical data, for an overall introduction to data analytics. Tools at all levels will be used, ranging from off-the-shelf desktop software to homegrown solutions.

This course is designed to introduce students to the current state of the art in data visualization. Upon completion of this course the student should have a basic understanding of key visualization techniques and theory with a focus on best practices. The course will introduce students to the principles of good design for visualization, methods for visualization of data from a variety of fields. Students will gain experience building and evaluating visualizations.

Course Material

• T. Munzner, Visualization Analysis and Design, A K Peters/CRC Press, 2015

Material Covered

• Git, GitHub, Jupyter Notebooks
• Languages and Tools
  • Python
  • R
  • Tableau
  • D3.js
• Data Visualization
• Story Telling and Critique
• Data Overview and Representation
• Marks and Channels
• Views
• Color
• Perception
• Dashboards
• Geographical Visualization
• Scientific Visualization (with VTK & ParaView)
• Sports Analytics

Grading

• Midterm Exam 25%
• Assignments 50%
• Final Project 25%