Continuing Education

CCTB465 - Machine Learning II - Advanced Algorithms

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Course Overview

Unlock your potential as a Machine Learning professional. This course builds upon the fundamentals explored in Machine Learning I and introduces algorithms that are at the cutting edge of Machine Learning research. Upon successful completion of this course, you will be able to describe and apply advanced Machine Learning techniques. Machine Learning is a form of Artificial Intelligence (AI) that provides systems the ability to use data to automatically learn from experience without being programmed. With the skills gained in this course, you will be able to explain advanced Machine Learning algorithms, and use Python libraries scikit-learn, TensorFlow, and Xgboost, to effectively apply and combine advanced algorithms.

It is recommended that you complete CCTB464 Machine Learning I prior to enrolling in this course.

Upcoming Offerings

This course is part of these programs or course groups:

Data Science


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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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