Course Description
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.
Fall 2024
Instructors
Meeting Patterns
Classes Start:
August 19, 2024
Classes End:
December 3, 2024
Distance Education:
Yes
Class Days:
W
Class Start Time:
6:00pm
Class End Time:
6:50pm
Class Type:
Lecture
Credits:
1.00
Restrictions:
None