DSI-606 Predictive Analytics 3 - Dimension Reduction, Clustering, and Association Rules - with R
In this course, students will cover key unsupervised learning techniques: association rules, principal components analysis, and clustering. Predictive Analytics 3 will include an integration of supervised and unsupervised learning techniques. The course includes hands-on work with R, a free software environment with capabilities for statistical computing. Graduate students enrolled in this course will complete a project/assignment that engages in higher levels of thought and creativity, requiring them to demonstrate knowledge at more advanced taxonomical levels.
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