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Machine Learning - Online Course

A 4-Day Livestream Seminar Taught by

Bruce Desmarais
Course Dates: Ask about upcoming dates
Schedule: All sessions are held live via Zoom. All times are ET (New York time).

10:30am-12:30pm ET (convert to your local time)
1:30pm-3:00pm ET

Watch Sample Video
Check out an exclusive 1-hour clip from Bruce Desmarais’s Machine Learning seminar, now on YouTube! 

The rapidly growing relevance of Machine Learning cuts across scientific disciplines in the humanities, social sciences, and natural sciences. It is increasingly used in research for predictive, explanatory, and exploratory purposes. Since 2022, Google Scholar has found approximately 441,000 scientific publications that included the phrase “machine learning.”

This course provides a comprehensive introduction to machine learning. Topics include: cross-validation, model evaluation, variable selection, classification, prediction, and regression.

Starting June 11, we are offering this seminar as a 4-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.

*We understand that finding time to participate in livestream courses can be difficult. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.

Closed captioning is available for all live and recorded sessions. Live captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.

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"I liked the mix of lectures, hands-on exercises, demonstrations, and the interpretation of R."

“I thought everything about this course was great! I liked the mix of lectures, hands-on exercises, demonstrations with screen-sharing, and the interpretation of R. I also liked the practical examples.”

Martha Mather

Kansas State University

“I liked that the instructor took the time to go over the software.”

“I liked that the instructor took the time to go over the software.”

Cyrus Mehta

Cytel Inc.