Continuing Education

CCTP461 - Machine Learning and Artificial Intelligence Bootcamp

Course Code

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Campus

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Course Overview

Discover how machine learning is used to create models that understand large amounts of data. Learn to use Python libraries for predictive problems (supervised learning) and for data clustering problems (unsupervised learning). Study major machine learning techniques such as multiple linear regressions (Ridge and Lasso), generalized linear models and classification, and clustering and dimensionality reduction methods. Please note that this course is offered by NAIT in partnership with RoboGarden. Accordingly, this outline originates from (was created by) RoboGarden. If you wish to read RoboGarden’s course outline, please follow this link: https://www.robogarden.ca/marketplace

Upcoming Offerings

This course is part of these programs or course groups:

Machine Learning and Artificial Intelligence


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Delivery Methods

  • Face to Face: Where: In-person meetings. When: Course is scheduled at a specific time for students to attend. Face-to-face instruction at all class meetings. Location may be on campus or at a worksite.
  • Blended: Where: Mixture of in-person & online components. When: Course is scheduled at a specific time for students to attend. Combination of face-to-face and online components at specific times. Some online components may be accessed online anytime.
  • Hyflex: Where: Choice to attend in-person or online meetings. When: Course is scheduled at a specific time for students to attend. For each class, students choose to attend in-person with the instructor or online at a specific time.
  • Remote Live Delivery: Where: Online with instructor. When: Course is scheduled at a specific time for students to attend. Instruction is delivered at set times online. Students do not come to campus.
  • Remote On-Demand Delivery: Where: Online anytime. When: No set class meetings. Coursework is accessed on-demand and online. While there are no set class meetings, there may be set due dates and deadlines for some activities. Students may interact with peers through virtual tools.
  • Remote Independent: Where: Online anytime. When: No set class meetings. Coursework is accessed on-demand and online, with no instructor support. While students choose when to do coursework, there may be set due dates and deadlines. 
  • Work Placement: Where: In-person meetings. When: Work is scheduled at a specific time for students to attend. Onsite work integrated learning. Location at a worksite.
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