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Machine learning (ML) is a fundamental component of artificial intelligence. Students will deconstruct the basic ideas behind popular ML algorithms, such as logistic regression or K-means, using a projects-centered approach. Students will create projects from successful ML use cases tailored to their specific domains of interest. Prerequisite skills and knowledge: Students should have basic knowledge of a programming language (e.g., R, Python, or others), experience with appropriate use of data structures (e.g., lists and matrices), and flow control mechanisms, such as loops. Students should also be familiar with matrix-vector multiplication and the norm of a vector.

Typically offered in Fall, Spring, and Summer