Loading...

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

Loading...

Enroll Now - Select a section to enroll in

Section Schedule
Date and Time TBA
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

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.

Required fields are indicated by .