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PMI CPMAI_v7 Exam Syllabus Topics:

Topic	Details
Topic 1	Data for AI: This domain targets the Data AI Lead and explores the central role of data in AI deployments, including Big Data concepts and unstructured data utility. It defines data governance strategies such as steering, stewardship, lifecycle mapping, lineage tracking, and master data practices.
Topic 2	Managing AI: This section is for the Project Manager and involves assessing model performance through quality assurance practices, validation techniques, overfitting and underfitting strategies, alignment with KPIs, and iterative refinements. It additionally covers the deployment of AI from training to inference, operationalization in production environments, on-premise or cloud resource selection, data lifecycle management, version control, and the choice of appropriate machine learning services.
Topic 3	Machine Learning: This section is aimed at the Data AI Lead and addresses practical machine learning applications. It begins with classification, clustering, and reinforcement algorithms, including ensemble methods and evaluation against business needs. Afterwards, it examines neural network architecture design and deep learning implementation across multiple problem types. Generative AI and LLMs follow, covering use-case suitability, limitations, operation explanations, prompt engineering, fine-tuning, and integrating these technologies into augmented intelligence solutions.

Reference: https://www.pmi.org/shop/tc/p-/digital-product/cognitive-project-management-in-ai-(cpmai)-v7---training-,-a-,-certification/cpmai-b-01

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