Course Details
Course Code: PMI-CPMAI; Duration: 3 Days; Instructor-led
Whether you’re already delivering AI initiatives or eager to start, this certification gives you the structure and credibility to turn innovation into measurable, lasting value.
With PMI-CPMAI you’ll learn how to:
- Turn bold AI visions into clear, achievable project plans
- Navigate fast-changing technologies without needing tool-specific training
- Unite cross-functional teams around a shared process
- Deliver outcomes that are ethical, measurable, and built to withstand business scrutiny
No matter your role (Project Manager, technologist, data expert, or consultant) PMI-CPMAI helps you grow your skills and your career in a market that rewards professionals and AI-savvy leaders.
Audience
- Project Manager
- Technologist
- Data expert
- Consultant
Prerequisites
There are no prerequisites required to attend this course.
Methodology
This program will be conducted with interactive lectures, PowerPoint presentation, discussion, and practical exercise.
Course Objectives
The course objectives are designed to help participants to:
- Turn bold AI visions into clear, achievable project plans
- Navigate fast-changing technologies without needing tool-specific training
- Unite cross-functional teams around a shared process
- Deliver outcomes that are ethical, measurable, and built to withstand business scrutiny
EXAM
The PMI-CPMAI exam will reflect the structure of this table while incorporating approaches for successful AI implementation. The concept of customizing approaches to contribute to the value of the CPMAI will be found throughout the five domain areas listed below and are not isolated to any domain.
- The exact number of questions for each domain may vary by form.
- Support Responsible and Trustworthy AI Efforts – 15%
- Identify Business Needs and Solutions -26%
- Identify Data Needs – 26%
- Manage AI Model Development and Evaluation – 16%
- Operationalize AI Solution – 17%
- Exam length: 120 Questions
- Exam time: 160 minutes
- Languages: English
Outlines
Module 1: The Need for AI Project Management
Discover why AI projects struggle, how iterative delivery supports success, and how CPMAI ensures ethical, effective outcomes.
Module 2: Matching AI With Business Needs (Phase I)
Align AI solutions and strategy to real business needs, assess feasibility, define ROI, and set clear project scope.
Module 3: Identifying Data Needs for AI Projects (Phase II)
Select the right data, ensure compliance, and build the infrastructure to support AI, laying the groundwork for effective AI data management across the project lifecycle.
Module 4: Managing Data Preparation Needs for AI Projects (Phase III)
Transform raw data into AI-ready inputs through quality checks, augmentation, and compliance controls.
Module 5: Iterating Development and Delivery of AI Projects (Phase IV)
Build and validate models, from machine learning to generative AI.
Module 6: Testing & Evaluating AI Systems (Phase V)
Test and monitor AI models, address drift, and ensure results are reliable, explainable, and aligned with goals.
Module 7: Operationalizing AI (Phase VI)
Operationalize AI responsibly, manage governance, and plan for continuous improvement.
