Course Information
Schedules
- 23 Nov 2026 (Mon) 7:00 PM - 10:00 PM
Registration period
21 Sep 2026 (Mon) - 22 Nov 2026 (Sun)
Price
HKD 14,000
(Course Fee: HKD14,000 includes PMI Certified Professional in Managing AI (PMI-CPMAI)™ Bundle)
(Course Fee: HKD14,000 includes PMI Certified Professional in Managing AI (PMI-CPMAI)™ Bundle)
Course Level
Study Mode
Duration
21 Hour(s)
Language
Cantonese, English
Location
Wanchai
Certificate
- Available
- (The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.)
Course Overview
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.
What You’ll Learn
The 21-hour PMI-CPMAI Exam Prep Course provides the knowledge and skills to pass the exam and manage AI projects effectively.
Organized around the six CPMAI methodology phases, it uses scenario-based exercises, case studies and a downloadable workbook to help you apply concepts immediately. The self-paced format includes multimedia content, a guided review of Exam Content Outline (ECO) references, and independent study activities—so you can learn at your own pace while building a strong understanding of the material.
Course contents:
- 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.
