LE/EECS 3404 (3.00)

Applied Machine Learning

Description

Machine learning is the study of algorithms that learn how to perform tasks or predict outcomes from prior experience. This course introduces students to basic machine learning concepts and algorithms in an accessible and application- oriented way. A project-based learning approach is used to explore how machine learning methods are used in diverse real-world applications and introduces students to popular machine learning toolkits, focusing on the programming required to build machine learning systems to solve practical problems. The course will also discuss potential limitations and risks of machine learning systems, including ethical issues, bias, data ownership and privacy. Course Credit Exclusions: LE/EECS 3405 3.00; LE/EECS 4404 3.00. Course Prerequisites: One of the following: LE/EECS 1516 3.00 or LE/EECS 2032 3.00 or LE/EECS 2031 3.00; One of SC/MATH 1025 3.00 or SC/MATH 1021 3.00.

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