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| Section | Weight | Objectives |
|---|
| Topic 1: AI Model Development and Iteration | | - Model building and validation
- 1. Machine learning / generative AI model development
- 2. Iterative delivery approach
|
| Topic 2: Identify Business Needs and Solutions | 26% | - Problem framing and business alignment
- 1. Define AI business objectives
- 2. Feasibility and ROI analysis
|
| Topic 3: AI System Testing and Evaluation | | - Model evaluation and monitoring
- 1. Performance evaluation and drift detection
- 2. Explainability and reliability assessment
|
| Topic 4: AI Operationalization and Governance | | - Deployment and lifecycle management
- 1. Continuous improvement and monitoring
- 2. AI governance and responsible AI
|
| Topic 5: Data Preparation for AI | | - Data cleaning and transformation
- 1. Feature engineering and preparation
- 2. Data quality assurance
|
| Topic 6: Data for AI | | - Data identification and governance
- 1. Data sourcing and selection
- 2. Data compliance and ethics
|
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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q98-Q103):
NEW QUESTION # 98
A data science team has produced working models through a series of ad hoc notebooks with hard-coded file paths and manually executed preprocessing steps.
What risk does this create for operationalization?
- A. The models will not achieve sufficient accuracy
- B. Accumulated technical debt prevents reliable, reproducible deployment
- C. The team will be unable to explain model predictions
- D. The data will not comply with retention policies
Answer: B
Explanation:
Manual, undocumented, and non-parameterized workflows cannot be reliably reproduced or automated in a production environment. This technical debt must be resolved through pipeline engineering before the model can be dependably operationalized.
NEW QUESTION # 99
A telecommunications company plans to operationalize a new AI-powered network optimization tool. The project manager needs to identify and map out all necessary tasks and associated resources. Which activity should the project manager perform?
- A. Conducting a feasibility study to assess the technical and financial viability
- B. Using a Gantt chart to schedule and monitor resource deployment timelines
- C. Developing a work breakdown structure (WBS)
- D. Applying an earned value management (EVM) methodology
Answer: C
Explanation:
Developing a work breakdown structure decomposes the AI operationalization work into manageable tasks and connects those tasks to the required resources, making it easier to define scope, responsibilities, and execution needs.
NEW QUESTION # 100
A national health insurance company is embarking on a complex AI project to assist in coordinating patient care across its multiple hospital network. The AI system will analyze large amounts of patient data to coordinate care, improve patient outcomes, and optimize resource allocation. Numerous healthcare providers' data needs to be integrated. The data includes patient information which is private. The project needs to comply with data privacy regulations in various countries. Which critical step should be performed to optimize representative training data?
- A. Enhance the key performance indicator (KPI) metrics.
- B. Improve data understanding and preparation.
- C. Implement comprehensive bias detection metrics.
- D. Increase the data set size without considering diversity.
Answer: B
NEW QUESTION # 101
In what way would you be using Generative AI if you used the results of the Generative AI solution to improve and accelerate your job?
- A. Used for Hyperpersonalization
- B. As an Augmented Intelligence system
- C. As a programmatic approach for automation
- D. As an autonomous system removing the human from the loop
Answer: B
NEW QUESTION # 102
Leadership wants a new HR system built that will better handle potential candidate matching. The project manager assigned to this project believes that the project is well-suited for AI, however they are unsure which pattern of AI this would be. What should the project manager do?
- A. Move forward without determining which patter of AI this falls under.
- B. Determine which pattern of AI this project falls under so they can best collect the data needed and skill sets for the team.
- C. Pick an algorithm that seems best suited for the problem and then determine which pattern of AI it is based on the algorithm selected.
- D. Conduct a straw poll with stakeholders to determine which pattern of AI this project falls under so they can best collect the data needed and skill sets for the team.
Answer: B
Explanation:
Identifying the AI pattern early helps guide data collection and team skill requirements, ensuring the project is aligned with the correct technical approach and business goals.
NEW QUESTION # 103
......
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