Will McMillan
William is an experienced cybersecurity professional and Microsoft-certified engineer with deep, practical knowledge of AI integration within security operations, threat detection, and automation workflows.
Courses
Types of AI
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.
Data Model Basics
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.
AI System Basics
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.
William is an experienced cybersecurity professional and Microsoft-certified engineer with deep, practical knowledge of AI integration within security operations, threat detection, and automation workflows.
He's designed and delivered technical training for enterprise environments covering topics such as AI-driven incident response, secure AI adoption, and data model governance.He has applied AI extensively within cybersecurity operations, particularly in threat detection, SOC automation, and incident response enrichment. His experience includes integrating GPT-based models and Azure OpenAI into Microsoft Sentinel workflows to summarize incident data, flag anomalies, and assist analysts with triage. He's also developed AI-assisted scripts for phishing analysis, log correlation, and vulnerability prioritization using Python and REST APIs. He has also contributed to AI risk assessments and data handling controls aligned with secure AI principles (prompt safety, model governance, and auditability).