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Скачать или смотреть How to Use CPMAI Framework to Execute AI Projects || Software Project Management

  • Technical Program Management Hub
  • 2025-11-25
  • 14
How to Use CPMAI Framework to Execute AI Projects || Software Project Management
Project ManagementAgileProgram ManagementTechnical Program ManagerInterview QuestionsScrum MasterPM ResourcesManagement Job SearchCPMAIAgentic AICPMAI FrameworkPMIAI Project Management
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How to Use CPMAI Framework to Execute AI Projects || Software Project Management

Delivering AI and Machine Learning projects requires more than traditional project management. In this short video, we break down the Cognitive Project Management for AI (CPMAI) methodology — a structured, vendor-neutral, and data-centric framework designed to help teams plan, execute, and operationalize AI initiatives with clarity and confidence.

CPMAI builds on proven approaches like CRISP-DM, while addressing practical realities unique to AI: iterative model development, data readiness, governance, and Responsible/Trustworthy AI considerations.

💡 In this video, you’ll learn:

What CPMAI is and why it’s widely used for AI/ML project execution

The six phases of the CPMAI lifecycle:

1. Business Understanding – Define objectives, stakeholders, and Trustworthy AI requirements; conduct AI Go/No-Go analysis
2. Data Understanding – Assess data sources, data quality, and feasibility
3. Data Preparation – Clean, transform, label, and structure datasets for modeling
4. Data Modeling – Select algorithms, tune hyperparameters, and experiment iteratively
5. Model Evaluation – Validate performance, align with business expectations, and ensure compliance
6. Model Operationalization – Deploy the model, implement governance, and establish continuous monitoring

🧩 Why CPMAI Matters:
AI projects often fail due to unclear business goals, poor data readiness, or lack of operational planning. CPMAI provides a clear, repeatable pathway for project managers, product teams, and data practitioners to deliver AI solutions responsibly and consistently.

📂 Perfect for:

New or aspiring AI project managers
Scrum masters and program managers entering AI/ML delivery
Teams transitioning from traditional software projects to AI initiatives
Anyone seeking a practical, structured approach to managing AI work

If you're looking to improve the success rate of AI projects in your organization, this concise overview is the place to start.

My Linkedin:   / jacinthp  
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Visit our website: https://www.programstrategyhq.com/
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Books I read and Refer for Project Management & Agile:
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Headfirst Agile: https://amzn.to/4aiMfoK
Agile Estimating and Planning: https://amzn.to/4jiUjKf
SAFe 5.0 Distilled: https://amzn.to/3WkUAmn
Inspired - Product Management: https://amzn.to/3WoHowO

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