Loading...

Course Description

Embark on a transformative learning journey where you'll explore the core principles of Artificial Intelligence (AI) and Machine Learning (ML). Machine learning is a branch of artificial intelligence that enables computers to learn and make decisions without explicit programming. It involves the development of algorithms that enable systems to analyze data, recognize patterns and improve performance over time. 

From the basics to more advanced techniques, you'll learn to identify opportunities for machine learning. You'll explore how to clearly define machine learning problems and use data science techniques to analyze and solve business problems. Our hands-on approach in this course focuses on tabular data, guiding you through the creation of supervised learning solutions. Gain expertise in the entire modeling process, from constructing classifications to evaluating models that solve business problems and elevate business strategies.

The course experience is designed and delivered in partnership with Braintoy, the creator of Canada's first low-code/no-code applied machine learning platform. It is well suited to individuals who are technically curious but not necessarily technically experienced. If you have an interest and aptitude for learning new technologies this course has been designed with you in mind. The course offers an applied experience using a low-code/no-code environment to build and evaluate supervised learning models. No prior programming experience is required. The course will provide you with a citizen developer skillset in supervised learning. A citizen developer skillset empowers individuals, typically with non-technical backgrounds, to create and customize solutions without extensive coding. It promotes agility, innovation and self-sufficiency within the workplace, allowing you to contribute actively to the development and improvement of solutions that support business functions within your current and future roles.

Note: Registration for this course closes two days before the course start date.

Learner Outcomes

Upon successful completion of this course, you'll be able to:

  • explain the purpose, applications and benefits of using python
  • install and run python programs
  • identify and use variables, operators, decision making statements and loops in python correctly
  • use operators to convert and manipulate different data types in python accurately
  • use functions and modules in python correctly
  • manipulate python program files, including read, write, delete and create files.

You’ll demonstrate your skill and knowledge acquisition through coursework and assessments during and after class.

To request a course outline, contact ConEdAdvising@sait.ca.

Earn a SAIT micro-credential

SAIT micro-credential badge

This course qualifies for the SAITMicro badge. Students who successfully complete this course with a final grade of A- (80%) or higher will earn a micro-credential and receive a shareable digital badge. Learn more.

To request a course outline, contact ConEdAdvising@sait.ca.

Prerequisites

There are no prerequisites for this course.

Applies Towards the Following Certificates

Loading...
Enrol Now - Select a section to enrol in
Section Title
Introduction to Machine Learning Citizen Development
Type
Lecture - Online Synchronous
Days
Th
Time
6:00PM to 7:00PM
Dates
Jan 09, 2025 to Feb 13, 2025
Schedule and Location
Contact Hours
30.0
Delivery Options
Blended  
Course Fee(s)
Tuition Fee non-credit $985.00
Section Notes

Prerequisites:
There are no prerequisites for this course.

Schedule: 

Participants will complete 24 hours of online, independent study supplemented with 6 hours of live virtual learning sessions with the instructor and other students. These virtual sessions are mandatory and will be delivered using Zoom & Brightspace/D2L and are interactive. Zoom sessions will be held on Thursdays starting January 9, 2025 and ending February 13, 2025, from 6:00 pm - 7:00 pm.

We encourage you to use your webcam and microphone to contribute to a more collaborative learning experience.

Required fields are indicated by .