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

Hours: 24
Credits: 1
Prerequisites: None
Corequisites: None

Additional information: This course is offered through ed2go. Find out more about ed2go courses.

ed2go courses


These 6-week online courses are designed for working professionals and those seeking personal advancement. From the start date, students have access to their courses 24/7. There are no live lectures or specific days and times students must be logged in. Each Wednesday and Friday, the instructor releases a lesson, for a total of 12. There is a 2-week period at the end of the course to complete the final exam.

Dates
Day/Time
Delivery
Campus
Cost
Availability
Start Date: Dec. 14, 2022
End date: Feb. 13, 2023
Day/Time:
Campus: Online
Cost: $185.00
Start Date: Jan. 18, 2023
End date: Mar. 20, 2023
Day/Time:
Campus: Online
Cost: $185.00
Start Date: Feb. 15, 2023
End date: Apr. 17, 2023
Day/Time:
Campus: Online
Cost: $185.00
Start Date: Mar. 15, 2023
End date: May. 15, 2023
Day/Time:
Campus: Online
Cost: $185.00

Registration dates

Not all courses are offered each term.

Winter 2023 registration opens November 28, 2022. Spring 2023 registration opens February 27, 2023.

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