Course description
This course will allow you to learn about specific techniques used in supervised, unsupervised, and semi-supervised learning, including which applications each type of machine learning is best suited for and the type of training data each requires. You will discover how to differentiate offline and online training and predictions, automated machine learning, and how the cloud environment affects machine learning functions. Additionally, you will explore some of the most significant areas in the field of machine learning research.
Course details
Additional information: This course is offered through ed2go. Find out more about ed2go.
ed2go courses
Choose from instructor-moderated or self-guided courses designed to fit your schedule. Build professional skills, explore a new interest, or advance your career with convenient online learning.
Ends: Dec. 14, 2026
Ends: Jan. 11, 2027
Ends: Feb. 15, 2027
Registration dates
Not all courses are offered each term.
Fall 2026 registration is open.Winter 2027 registration opens November 2, 2026.
Delivery options
In person: classes held in person on a campus/site in a classroom/lab/shop/studio for the course duration
Online - Asynchronous: 100% online delivery, no scheduled day or time course requirements with the instructor, assigned due dates
Online - Synchronous: 100% online delivery, scheduled day and time course requirements with the instructor, assigned due dates
Hybrid: any combination of in person, timetabled, on campus, online, and hyflex delivery