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Predictive Analytics 3 – Dimension Reduction, Clustering and Association Rules No ratings yet.

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From Statistics.Com:

“Data mining, the art and science of learning from data, covers a number of different procedures. In this online course, “Predictive Analytics 3 – Dimension Reduction, Clustering, and Association Rules,” you 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.

This is a hands-on course — participants in the course will have access to an Excel-based comprehensive tool for data-mining, XLMiner, the use of which will be explained in the course. 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 predictive Analytics 1 and 2 (though the unsupervised methods taught in the rest of the course stand on their own and can be studied without having taken those courses).”

Recommended Prerequisites: Statistics, Probability and Study Design, Inference and Association.
Predictive Analytics 1 at Statistics.com

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