Will McMillan

This course will teach you how to use AI copilots safely and responsibly in real-world investigations. You will learn how to combine human judgment with AI speed, apply governance frameworks, identify AI-specific threats, and measure tangible improvements in performance and accuracy.

Artificial Intelligence is reshaping how organizations make decisions, build products, and serve customers. Yet for every success story, there are many AI projects that fail compliance reviews, stall before launch, or create new risks because teams lacked clear, actionable best practices. This course was created to bridge that gap.

Every successful AI initiative, regardless of size or complexity, follows a repeatable process known as the machine learning (ML) lifecycle. Learn the phases of a typical ML lifecycle and why adopting one is the single most important factor in delivering reliable, ethical, and cost-effective AI solutions.

Artificial Intelligence is not a single system or tool. It's a collection of different methods that learn, reason, and solve problems in unique ways. Each type of AI has its own strengths, limitations, and data requirements. Learn how these types differ, when to use each, and what tradeoffs are most important in production systems.

Before any algorithm is trained or deployed, its success depends on one thing: the shape and structure of the data feeding it. This course establishes the foundation for understanding why data modeling (how information is organized, related, and represented) is the most critical stage of any AI or machine learning (ML) project.

Artificial Intelligence has moved from the realm of research into the everyday reality of business and IT. Most professionals now use AI-powered tools in their work, but many still misunderstand what an AI system actually is. This course defines what we mean by an AI system and shows how these systems fit into enterprise architectures.