Ecampus Schedule of Classes - All Terms

College of Engineering

CS 432 – Introduction to Applied Machine Learning (4)

Explores and applies machine learning models and methods including unsupervised learning and supervised learning. Focuses on gathering, cleaning, and preparing data for various analyses. Distinguishes between unsupervised methods including clustering, and dimensionality reduction and supervised modeling methods including Decision Trees, Random Forest, Naive Bayes, Support Vector Machines, and Regression). Covers Training and Testing, Confusion Matrices, x-fold cross validation, visualization options, decision science, ethical considerations, and data communication. Uses Python, Sklearn, and related Python packages/libraries. This course may be subject to Enforced Prerequisites that restrict registration into the course. Check the offerings below for more information.

For more information, contact OSU Ecampus at 800-667-1465 (option 1) or ecampus.ess@oregonstate.edu.

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