Understanding AI Data
Course
Description
The results AI produces are only as good as the data behind it. Yet many professionals working with AI don’t fully understand how data determines outcomes. Our Understanding AI Data course shows you how data powers machine learning and generative AI, and why quality data is vital to successful AI projects. You’ll explore every stage of the AI data lifecycle and learn how to spot risks like bias and data drift so you can evaluate data-related challenges and get more out of the AI systems you use.
For the best learning experience, take AI Foundations (CEAI 1001) and Responsible AI (CEAI 1002) before this course.
Course at a glance
Course code: CEAI 1003
Format: Online
Duration: 30 hours
Language: English or French
Upskill your team with custom corporate training.
Key takeaways
- Understand the role of data in modern AI systems, including traditional machine learning, Generative AI, and autonomous AI systems
- Recognize the major types of data used in AI projects and how they differ
- Assess common data quality issues in AI projects, including bias, representation, and data limitations
- Describe the AI data lifecycle, from data collection and preparation through storage and post-deployment monitoring
- Evaluate data requirements and data-related risks across different AI use cases, including predictive and Generative AI application
