PMI Certified Professional in Managing AI (PMI-CPMAI)™ Certification Training
- 3 Days Course
- Language: English
Introduction:
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.
This course will earn you 21 PDUs
Objectives:
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
Course 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
Enroll in this course
£1,995.00