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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Operationalize AI Solution | 17% | - Establish monitoring, maintenance, and improvement processes - Manage change, adoption, and governance post-launch - Deploy AI systems into production |
| Topic 2: Manage AI Model Development and Evaluation | 16% | - Oversee model design, training, and validation - Address model drift, explainability, and limitations - Monitor performance, accuracy, and reliability |
| Topic 3: Identify Data Needs | 26% | - Plan data collection, storage, and infrastructure - Define data requirements and sources - Ensure data quality, privacy, security, and compliance |
| Topic 4: Identify Business Needs and Solutions | 26% | - Align AI initiatives with organizational strategy - Evaluate feasibility and value of AI solutions - Define requirements, scope, and success criteria |
| Topic 5: Support Responsible and Trustworthy AI Efforts | 15% | - Ensure fairness, transparency, accountability - Manage bias, risk, compliance, and societal impact - Establish ethical and governance frameworks |
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NEW QUESTION # 188
A project manager overseeing an AI project is concerned about potential data privacy violations.
Before progressing further with the project, what should the project manager do to address this concern?
Answer: B
Explanation:
Conducting a thorough compliance audit against applicable data regulations is the appropriate step before progressing because it verifies whether the project's data collection, processing, storage, access, and usage practices meet privacy and regulatory requirements.
NEW QUESTION # 189
A healthcare organization plans to use an AI solution to predict patient readmissions. The data science team needs to identify data sources and ensure data quality. Which method will meet the project team's objectives?
Answer: D
Explanation:
Operationalizing a data catalog helps identify available data sources and maintain consistent metadata standards. This supports data discovery, ownership, lineage, relevance, and quality management for patient readmission prediction.
NEW QUESTION # 190
An organization needs a document classification capability. A commercial service already provides this function at acceptable accuracy, while an internal build would take an estimated nine months.
What should the project manager evaluate first?
Answer: D
Explanation:
Build decisions are justified when the capability provides differentiation that a commodity service cannot deliver. If the function is not a differentiator, buying conserves resources for work that creates distinct organizational value.
NEW QUESTION # 191
You are working on the data engineering pipeline for the AI project and you want to make sure to address the creation of pipelines to deal with model iteration. What part of the pipeline best deals with this step?
Answer: A
Explanation:
Retraining pipelines automate the process of updating models with new data, enabling continuous iteration and improvement of AI models.
NEW QUESTION # 192
During CPMAI Methodology Phase IV: Model Development, which of the following is not done during this phase?
Answer: B
Explanation:
Model selection typically occurs after development, during the evaluation and validation phase, rather than during the Model Development phase where algorithms are selected, trained, and tuned.
NEW QUESTION # 193
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