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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identify Business Needs and Solutions | 26% | - Align AI initiatives with organizational strategy - Define requirements, scope, and success criteria - Evaluate feasibility and value of AI solutions |
| Topic 2: Operationalize AI Solution | 17% | - Establish monitoring, maintenance, and improvement processes - Manage change, adoption, and governance post-launch - Deploy AI systems into production |
| Topic 3: Identify Data Needs | 26% | - Define data requirements and sources - Ensure data quality, privacy, security, and compliance - Plan data collection, storage, and infrastructure |
| Topic 4: Manage AI Model Development and Evaluation | 16% | - Monitor performance, accuracy, and reliability - Oversee model design, training, and validation - Address model drift, explainability, and limitations |
| Topic 5: Support Responsible and Trustworthy AI Efforts | 15% | - Ensure fairness, transparency, accountability - Establish ethical and governance frameworks - Manage bias, risk, compliance, and societal impact |
>> New CPMAI Exam Questions <<
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NEW QUESTION # 66
A healthcare project manager is evaluating whether to implement an AI-powered diagnostic tool.
The initial cost is US$500,000 with an expected return on investment (ROI) of 15% within the first year. The project needs to satisfy multiple stakeholders including hospital administrators and medical staff. Which method will maximize a positive ROI for the AI implementation?
Answer: A
Explanation:
Monitoring AI model performance against key performance indicators helps confirm that the diagnostic tool is producing measurable business and clinical value after implementation.
Tracking outcomes such as diagnostic accuracy, workflow efficiency, cost savings, and adoption supports adjustments that improve the likelihood of achieving a positive return on investment.
NEW QUESTION # 67
You are working with a dataset that has a high number of dimensions. You're running into issues because some dimensions don't have enough real examples to properly train the systems for predictable results.
What's your best course of action?
Answer: A
NEW QUESTION # 68
An AI governance review requires ensuring that all model decisions can be traced and justified during audits. The organization must demonstrate accountability to regulators and stakeholders.
Which mechanism should the project manager implement to meet this requirement effectively?
Answer: B
Explanation:
Audit trails and documentation provide traceability, essential for governance and accountability.
NEW QUESTION # 69
During the evaluation of an AI solution, the project team notices an unexpected decline in model performance. The model was previously achieving high accuracy but has recently shown increased error rates. Which action will identify the cause of the performance decline?
Answer: C
NEW QUESTION # 70
You are working for a large multinational organization and have been assigned to a new project.
For your new ML project you need to make sure you're managing data privacy and security as you're working with sensitive customer data.
What critical security issues do you need to make sure you address (Select all that apply.):
Answer: A,B,C,D
NEW QUESTION # 71
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