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DSI-6030 Predictive Analytics 3 - Dimension Reduction, Clustering, and Association Rules - with Python

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 Python, 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.

Credits: 3

Offered in Jan 2024, May 2024, Sep 2024, Jan 2025, May 2025

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(Please visit the University bookstore to view the correct materials for each course by semester as the contents of the actual online syllabus may differ from the preview due to updates or revisions)