course | Cognitive Project Management in AI (CPMAI)™ v7 Certification Bootcamp
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DIGTR-2541 | Cognitive Project Management in AI (CPMAI)™ v7 Certification Bootcamp
Course Sector : Digital Transformation and Innovation
| Duration | Date from | Date to | Course Venue | Course fees | Book a course |
|---|---|---|---|---|---|
| 5 Days | 2025-11-10 | 2025-11-14 | Dubai | $4,250 | Book now |
| 5 Days | 2025-06-16 | 2025-06-20 | London | $4,950 | Book now |
| 5 Days | 2025-07-14 | 2025-07-18 | Abu Dhabi | $4,250 | Book now |
Course Introduction
This immersive bootcamp equips project managers, technologists, and business leaders with the knowledge and skills to confidently lead AI, ML, and cognitive projects using PMI’s vendor-neutral CPMAI™ methodology. Over five intensive days, participants will traverse AI fundamentals, data lifecycle management, and deployment strategies while mastering best practices for building trustworthy, data-driven AI solutions. Designed around the CPMAI v7 Examination Content Outline, the course blends theory, real-world case studies, and hands-on activities to ensure preparedness for both AI leadership roles and certification success
Course objective
- Demonstrate AI fundamentals, key patterns, and ML models
- Apply CPMAI methodology with best practices for iterative AI development
- Understand data processes, governance, and pipeline engineering
- Proactively manage AI project-specific risks and stakeholder engagement
- Incorporate principles of Trustworthy & Responsible AI
- Prepare strategically to pass the PMI CPMAI™ v7 certification exam
Course Outline | DAY 01
AI Foundations and Project Context
- Introduction to AI, cognitive technologies, and machine learning
- Understanding the differences between AI, ML, DL, and automation
- Business drivers and AI adoption challenges
- The Seven Patterns of AI: use cases and business alignment
- Overview of the CPMAI™ v7 framework and its value in structured AI delivery
Course Outline | Day 02
Phases I–III of CPMAI™ – Project Initiation and Data Understanding
- CPMAI Phase I: Business understanding and problem definition
- Stakeholder mapping, project chartering, and Go/No-Go decision points
- CPMAI Phase II: Data understanding and data collection
- CPMAI Phase III: Data preparation, cleansing, and compliance
- Data governance principles, privacy regulations, and security readiness
Course Outline | Day 03
Phases IV–V – Modeling and Evaluation
- CPMAI Phase IV: Building and training machine learning models
- Overview of supervised vs. unsupervised learning
- Tools and platforms for AI model development (low-code/no-code options)
- CPMAI Phase V: Model evaluation, testing, and iteration cycles
- Addressing bias, explainability, and performance metrics
Course Outline | Day 04
Phase VI – Deployment and Operationalization
- CPMAI Phase VI: Deployment planning and lifecycle management
- Monitoring AI model performance in production (drift, accuracy, feedback loops)
- AI operations (AIOps), MLOps, and infrastructure readiness
- Integrating AI into business workflows and enterprise systems
- Addressing change management and user adoption challenges
Course Outline | Day 05
Phase VI – Deployment and Operationalization
- CPMAI Phase VI: Deployment planning and lifecycle management
- Monitoring AI model performance in production (drift, accuracy, feedback loops)
- AI operations (AIOps), MLOps, and infrastructure readiness
- Integrating AI into business workflows and enterprise systems
- Addressing change management and user adoption challenges
BOOST’s Professional Attendance Certificate “BPAC”
BPAC is always given to the delegates after completing the training course,and depends on their attendance of the program at a rate of no less than 80%,besides their active participation and engagement during the program sessions.
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