96-837 Visual Analytics
This course is project-oriented and is intended to give students substantial hands-on, learning-by-doing experience with software tools that offer both analytical (machine learning, statistics, data mining,...) and visualization capabilities. The instructor will propose, for class projects, suitable data sets and projects from among publicly available, on-line repositories. Students are also invited to bring their own data sets, or identify - with help of instructor and fellow students - data sets that are interesting for visual analytics. Using data analysis and visualization tools from the Statistical (software includes R, SAS), Business (MS Excel, OpenOffice Calc), and/or Machine learning (Weka, Genie/Smile) communities, students will then undertake a significant learning-by-doing team project, informed by lectures and project meetings.
Credit units: 12
Prerequisite(s): Students should be comfortable with computer programming.