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Course Description

This course will equip you with the fundamental machine learning (ML) and artificial intelligence (AI) algorithms and techniques for mining and analyzing data, and extracting insights for data-driven decision making. You will learn how to formulate a ML/AI problem, prepare data, build and optimize predictive models using a wide range of algorithms and evaluate the performance of those models. Throughout the course you will use Scikit-learn and TensorFlow hands-on to build applications that learn from data.

The Data Science courses are also offered online in partnership with University of Waterloo - WatSPEED. 

3586 - Machine Learning - ONLINE

Note: If you wish to apply the 3586 - Machine Learning - ONLINE completed at University of Waterloo - WatSPEED towards the Certificate in Artificial Intelligence at School of Continuing Studies, please follow the Prior Learning Application form on SCS website.

 

Learning Outcomes

  • Formulate machine learning and AI problems
  • Learn techniques to pre-process data for modeling 
  • Train generalized predictive classification and regression models
  • Identify clusters in data such as market segments
  • Evaluate and combine models for best performance

Notes

Previously titled Analytic Techniques & Machine Learning

Prerequisites

3250 - Foundations of Data Science and 3251 - Statistics for Data Science,  OR

Previous knowledge and experience in Python programming and Statistical techniques, OR

A passing grade on a self-assessment test/quiz for equivalent skills.

Recommendations

Laptop Computer with the following Specifications:
System Type: 64 bit operating system, X 64-based processor; Windows 7, 8 or 10; Mac OS/X or Linux running on similar hardware.  Processor: Intel ® i5-3230M CPU @ 2.6 GHz or better; Installed Memory ( RAM): 8 GB or more.

Software needed for this course is free and mostly open source.  You will receive instructions for download/install/use in class

Academic Requirements:  A degree in Engineering, Mathematics, or Computer Science is recommended, but not required. Basic knowledge of programming and programming languages is also recommended.

This course may be applied towards the SCS Certificate(s) in

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Enroll Now - Select a section to enroll in

Language of Delivery
English
Type
In-Class
Days
M
Time
6:00PM to 9:00PM
Dates
Sep 14, 2026 to Dec 07, 2026
Schedule and Location
View Details
Contact Hours
36.0
Campus
  • St. George Campus
Delivery Options
IN-CLASS  
Course Fees
Flat Fee non-credit $1,199.00 Click here to get more information

Section Notes

No class on Thanksgiving Day, Monday, October 12, 2026.

Textbooks are required for this class.

Go here for instructions on how to order your textbook.

This in-class course uses Quercus (UofT Learning Management Engine) to post course materials.

Go here for information on when you will receive your access information.

For technical requirements, please go here.

Language of Delivery
English
Type
Online with Real Time Meetings
Days
Th
Time
6:00PM to 9:00PM
Dates
Sep 24, 2026 to Dec 10, 2026
Schedule and Location
View Details
Contact Hours
36.0
Delivery Options
ON-LINE  
Course Fees
Flat Fee non-credit $1,199.00 Click here to get more information
Instructors

Section Notes

Textbooks are required for this class.

Go here for instructions on how to order your textbook.

You will receive login information for your online classroom, Quercus (UofT Learning Management Engine) via email.

Go here for information on when you will receive your access information.

For technical requirements, please go here.

Required fields are indicated by .