Practical Data Analysis using Machine Learning COMP 9723

New
Online Option

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-world problems and data, including your own.

Note(s)

Course Delivery Method:

This is normally an in-class course but will be offered temporarily online while college buildings are closed.

Technical/Computer Requirements:

You will be required to have regular access to the Internet.

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)

Contact Information

Course Sections

CRN:
W51814
Delivery Method: In-class

Some courses require you to purchase a textbook. The cost of the textbook is not included in the course fee unless otherwise indicated. If there is a textbook assigned for this course, it will be listed on the bookstore website.