Practical Data Analysis using Machine Learning COMP 9723

Blended

Our Practical Data Analysis using Machine Learning course explores several methods and algorithms used to perform regression, classification and clustering tasks. Study such powerful methods as support vector machines, decision trees, random forests, naïve Bayes classifiers and the k-nearest neighbours algorithm. Get an introduction to neural networks, how they work and what they can do, and practice building several artificial neural network models. This data analysis course also gives you the opportunity practice different evaluation techniques for the statistical models you develop since evaluating statistical models is one of the most important and crucial steps in any data analysis task. Develop your understanding of data analysis fundamentals by working with real work problems and data, including your own.

Note(s)

Course Delivery Method:

This course is delivered through a blended model that combines online and on campus environments, rotating on a weekly basis. The first class will be held on campus.

Prerequisites

You must have completed our COMP 9721 Introduction to Machine Learning course.

Hours and Fees

Hours

42

Fee

$334, includes a non-refundable materials fee of $25

Course Sections

There are no classes currently scheduled for this course; however, check back often to see if we have developed additional schedules for the upcoming term. If you would like to receive an email update when the fall term (September to December) begins and when the 2023–24 academic year (September 2023 to August 2024) becomes available and open for registration, complete our notification sign-up form.
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Technology Department
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Read about our textbooks policy, and remember that the Continuing Education attendance policy and closure dates differ from those for full-time college programs.