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Course

Understanding AI Data

Check Upcoming Dates
Course code
CEAI 1003
Duration
30 hours
Artificial Intelligence (AI) doesn’t exist without data. In 2006, British mathematician Clive Humby said, “Data is the new oil.” And data is the fuel that powers AI. However, having data is not enough, you need good data. But how can you identify quality data in the AI world? This course provides the answer.

The first part of the course will help you identify good data, spot potential biases, and interpret graphs and other visualizations from data. The second part of the course will focus on the practical aspects of data for AI projects. This section will help you assess data requirements for AI projects, differentiate between various storage methods, and identify data sources. Upon completion of the course, you will grasp the single most important aspect of AI—data.

To help you develop data skills for AI, you will be exposed to case studies and other projects that resemble data-related situations AI professionals face daily. During these exercises, you will examine the different steps of the data lifecycle to help you assess data quality and the requirements for various AI projects. The assignments will position you as the domain expert and client on an AI project and teach you how to work alongside a data scientist. Are you up for the challenge?

This is an online, synchronous course.

We recommend taking the AI Foundations (CEAI 1001) and Responsible AI (CEAI 1002) before taking this course.

Upcoming date(s)

Term
Section
mode
Fees

January 14 – March 18, 2025
Tu 18:00 – 21:00
Winter
1
Online
$800.00
Term
Winter
Section
1
mode
Online
Fees
$800.00

April 1 – June 3, 2025
Tu 18:00 – 21:00
Spring
1
Online
$800.00
Term
Spring
Section
1
mode
Online
Fees
$800.00

January 13 – March 17, 2026
Tu 18:00 – 21:00
Winter
1
Online
$840.00
Term
Winter
Section
1
mode
Online
Fees
$840.00

March 31 – June 2, 2026
Tu 18:00 – 21:00
Spring
1
Online
$840.00
Term
Spring
Section
1
mode
Online
Fees
$840.00

Your takeaways

This course is a great way to help you:
• Explain the importance of "good" data in AI projects
• Describe the different types of data used in AI projects
• Identify the different techniques used to handle and store data in AI
• Assess what is required to carry out an AI project

Our approach

This fully online course employs a project-based approach that focuses on the acquisition of practical real-world skills in AI. You will learn directly from industry professionals and receive individualized feedback. You will have the opportunity to go beyond AI theory by actively participating in assignments aimed at using AI for problem-solving.

Who benefits the most?

• Tech enthusiasts who want to add AI to their skill set
• Leaders with financial, operational, or technological responsibilities who are interested in adopting AI
• Managers who want to better support their technical AI employees or who may be involved in AI projects
• Employees in different industries who want to learn how AI solutions can help solve problems or want to contribute to their organization’s AI initiatives more meaningfully
• Students who want to prepare themselves for an AI workforce or explore AI as a potential career path
• Anyone who wants to learn the fundamentals of AI
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