Most AI initiatives never reach production because they are run like software projects instead of data projects. CPMAI™ — now part of PMI — is the only widely adopted methodology built specifically for AI and machine-learning delivery: six iterative phases that start from business understanding and data understanding, not from the model.
What machine learning can and cannot do, model types, and how AI projects differ from software projects.
Framing an AI use case, feasibility screening, data availability and quality assessment.
Labelling, pipelines, training/validation splits and iteration discipline.
Business-relevant metrics, drift monitoring, MLOps handover and governance.
Full timed mocks plus a real use case run end-to-end through the six phases.
An exam-focused guide to managing AI projects using practical, data-centric and governance-aware approaches.
Six realistic mock exams for professionals preparing to manage AI projects confidently.
Cognitive Project Management for AI — a six-phase, iterative methodology for running AI and data projects, now offered through PMI.
For delivery roles, yes. Generic certificates teach tools; CPMAI teaches how to scope, govern and operationalise AI work.
No. CPMAI is a management methodology; you need to understand data workflows, not build models yourself.
Yes — PMP gives you governance and stakeholder control, CPMAI gives you the AI-specific lifecycle. Together they cover most AI programme needs.
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