PMI Certified Professional in Managing AI (PMI-CPMAI)™ Certification Training

AI is changing how organizations develop products, improve operations, serve customers, and make decisions. But implementing AI successfully takes more than technical capability. Organizations need professionals who can evaluate opportunities, set clear business objectives, coordinate diverse teams, manage data and development challenges, address governance and ethical considerations, and turn AI investments into measurable results.

PMI-CPMAI certification training gives you a structured framework for doing exactly that. Prepare for the exam, build practical AI project management skills, and position yourself to lead one of the fastest-growing categories of projects in today's workplace.

How You Will Benefit

• Translate AI opportunities into achievable project plans
• Align AI initiatives with clearly defined business needs
• Determine whether AI is an appropriate solution to a business problem
• Coordinate business, project, data, and technical stakeholders
• Identify and manage the data requirements of AI initiatives
• Guide iterative development and delivery
• Evaluate AI solutions against business and technical objectives
• Address governance, ethics, transparency, and responsible AI considerations
• Operationalize AI solutions and support continuous improvement
• Manage AI initiatives without relying on a specific technology, platform, or AI tool

What You Will Learn

By the end of this course, participants will be able to:

• Learn how to lead AI projects without coding
• Gain familiarity with the tool-agnostic CPMAI methodology
• Master the art of guiding AI development and evaluation
• Understand responsible AI usage and governance
• Begin translating technical complexity into business value

Who Should Attend

PMI-CPMAI certification training is designed for professionals who manage, contribute to, advise on, or want to lead artificial intelligence initiatives. No prior AI development experience is required to pursue the PMI-CPMAI certification.

Guaranteed To Run

All PMI-CPMAI exam prep courses are 100% guaranteed to run on the listed dates. Yes, even if there's only one student. While other providers often postpone courses due to low enrollment, we promise to never do that.

Format

Virtual Classroom: 3 days of web-based eLearning with a live instructor. To help assimilate the tools and techniques learned, there is a mixture of individual and group exercises throughout the course. Students need to be prepared for a high level of participation.

In-House: If you have 10 or more employees seeking training, we will deliver the course at your facility or in a private virtual session.

Duration

3 Day(s) | 21 PDUs | 2.1 CEUs

Outline

Introduction

• Course Overview
• Learning Objectives
• Introduction to the PMI-CPMAI Exam

The Need for AI Project Management

• Why AI Now?
• The Seven Patterns of AI
• Why AI Projects Fail
• Fears & Concerns of Trustworthy AI
• Layers of Trustworthy AI
• Iterative and Adaptive Approaches for AI
• Cognitive Project Management for AI

Matching AI with Business Needs

• Determine the Problem You Are Solving and if AI is a Good Fit
• Evaluate AI Feasibility
• Map Business Problems to AI Patterns
• Determine AI Go/No-Go
• Determine AI Project ROI and Success Metrics
• Scope and Schedule AI Projects
• Determine Needs for the AI Project Team
• Determine Project-Specific AI Risks
• Learn How All This Maps to PMI-CPMAI™ Phase I

Identifying Data Needs for AI Projects

• The Role of Data in AI
• Determine Data Quality and Quantity Requirements for AI
• Determine Data Sets for AI Projects
• Understand Data Privacy, Compliance, and Access Requirements
• Coordinate Data Infrastructure and Access Needs
• Analytics and Key Data Roles
• Learn How All This Maps to PMI-CPMAI™ Phase II

Managing Data Preparation Needs for AI Projects

• Data Preparation for AI Projects
• Data Pipeline in AI Projects
• Data Quality Check and Verification
• Data Transformation and Synthetic Data
• Data Augmentation and Labeling for AI
• Data Management for Generative AI Systems
• Trustworthy AI in Data Preparation
• Learn How All This Maps to PMI-CPMAI™ Phase III

Iterating Development and Delivery of AI Projects

• Machine Learning and Models
• Model Development
• Model Validation
• Building Generative AI Systems
• Learn How All This Maps to PMI-CPMAI™ Phase IV

Testing and Evaluating AI Systems

• Model Evaluation
• Model Iteration
• Model Performance, Data and Model Drift
• Evaluating Models Against Business and Technology KPIs
• AI System Monitoring and Management
• Explainable and Interpretable AI System
• Learn How All This Maps to PMI-CPMAI™ Phase V

Operationalizing AI

• Moving AI Models into Operations
• AI Platforms and Infrastructure
• Ways to Interact with AI Models
• Operationalizing Generative AI
• Model Life Cycle Management
• AI and Model Governance
• Trustworthy AI Considerations in Operations
• Limits of AI
• Moving to the Next Iteration After PMI-CPMAI™ Phase VI

Course Closeout

• Course Summary
• Next Steps for Taking the Exam
• Wrap-Up