PMI Certified Professional in Managing AI (PMI-CPMAI)® Exam Preparation Course

• Official PMI-CPMAI® Application Eligibility: Fulfill the complete 21-hour formal training requirement needed to apply for the PMI-CPMAI® exam.
• Exam-Aligned Mastery: Gain direct mastery of the official PMI-CPMAI® Examination Content Outline using exclusive curriculum developed directly by the Project Management Institute (PMI).
• Practical AI Implementation: Acquire hands-on knowledge to design, deploy, and manage AI and machine learning projects safely, ethically, and effectively.
• Certified Expertise: Gain the confidence and practical framework to pass the certification exam on your first attempt and lead complex AI initiatives.
• Verified Quality: Learn directly from ALTAWAIL, a recognized PMI Authorized Training Partner (ATP), ensuring high-standard, vetted instruction.

• Support responsible, trustworthy, transparent, and ethical AI efforts.
• Identify business needs, project feasibility, scope, and ROI.
• Determine data requirements, sources, infrastructure, and privacy needs.
• Oversee data transformation, quality verification, and preparation.
• Oversee algorithm selection, model training, and QA/QC protocols.
• Conduct bias audits and verify model readiness (Go/No-Go).
• Manage deployment, model governance, performance monitoring, and drift.
• Develop operational transition, incident response, and contingency plans.

• Project Managers and PMO Leaders aiming to specialize in AI-driven projects.
• Data Science and IT Team Leads transitioning into project management roles.
• Professionals seeking PMI-CPMAI® certification to validate their AI project leadership skills.

• AI Project Lifecycle Management.
• Responsible and Ethical AI Governance.
• Business Value and ROI Alignment.
• Data Strategy and Quality Assessment.
• AI Model Development Oversight.
• AI Bias and Fairness Auditing.
• MLOps and AI Model Governance.
• AI Risk Management and Contingency Planning.

• Practical case studies.
• Workshops and group activities.
• Role-playing.
• Experiential learning and brainstorming.
• Mental challenges and team competitions.
• Training videos and demonstrations.
• Simulation-based learning and games.

If a participant already holds a PMI certification, this course may qualify for PDUs. The final allocation across Ways of Working, Power Skills, and Business Acumen will be based on the approved course content and PMI reporting requirements.

• Prerequisite Experience: None (No prior project management, AI/ML, or coding experience required).
• Educational Background: None (No specific high school diploma or university degree required).
• Mandatory Training: Completion of the official PMI-CPMAI® Exam Prep Course.
• Age Requirement: Must be at least 18 years old.

1. Fulfill the Eligibility Requirements

   Confirm that you are at least 18 years old. No university degree or prior coding or project management experience is required.

2. Complete the PMI-CPMAI® Exam Preparation Program

   Attend the training sessions and complete the required activities to receive a certificate confirming 21 hours of specialized training.

3. Submit Your Application to PMI

   Create an account on PMI.org, document the required training hours, and submit the application for review.

4. Complete the Audit Process if Selected

   Provide the required documentation to verify completion of the training and the age requirement.

5. Schedule and Take the Exam

   After application approval and payment, schedule and take the exam using one of the available authorized testing options.

6. Earn and Maintain the Certification

   Pass the exam to earn the PMI-CPMAI® certification. To maintain it, earn and report 30 PDUs during each three-year renewal cycle and complete PMI renewal requirements.

• Oversee privacy and security plan.
• Manage AI/ML transparency.
• Conduct bias audits.
• Monitor regulatory and policy compliance.
• Manage accountability documentation and audit trail.

• Identify problem to solve.
• Evaluate initial feasibility.
• Perform risk assessment.
• Develop project scope statement.
• Determine return on investment (ROI).
• Manage adoption and integration risk.
• Draft AI solutions.
• Define success criteria.
• Support business case creation.
• Determine project resources.

• Identify data required.
• Identify data subject matter experts.
• Identify data locations and sources.
• Coordinate infrastructure and environment.

• Collect data required.
• Verify data privacy and compliance.
• Oversee data assessment.
• Determine data fit for solution (Go/No-Go).
• Translate data insights to leadership.

• Oversee modeling and algorithm techniques.
• Oversee QA/QC.
• Manage model training.
• Manage data transformation and preparation.
• Verify data quality (Go/No-Go) and verify model readiness (Go/No-Go).

• Manage deployment plan creation.
• Manage deployment execution.
• Oversee model governance.
• Oversee metrics.
• Prepare final report and lessons learned.
• Manage operational transition plan.
• Oversee contingency planning.

Note: The percentages shown represent the approximate weight of each domain in the PMI-CPMAI® exam and do not represent the distribution of course hours.