In this course, you will cover key unsupervised learning techniques including association rules, principal components analysis, and clustering. You will also review integration of supervised and unsupervised learning techniques.
Participants will apply data mining algorithms to real data, and will interpret the results. A final project will integrate an unsupervised task with supervised methods covered in our Predictive Analytics 1 and Predictive Analytics 2 courses. This course uses Analytic Solver Data Mining (previously called XLMiner), a data-mining add-in for Excel.