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PMI CPMAI Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Manage AI Model Development and Evaluation	16%	- Monitor performance, accuracy, and reliability - Address model drift, explainability, and limitations - Oversee model design, training, and validation
Topic 2: Identify Business Needs and Solutions	26%	- Evaluate feasibility and value of AI solutions - Define requirements, scope, and success criteria - Align AI initiatives with organizational strategy
Topic 3: Identify Data Needs	26%	- Ensure data quality, privacy, security, and compliance - Plan data collection, storage, and infrastructure - Define data requirements and sources
Topic 4: Operationalize AI Solution	17%	- Deploy AI systems into production - Manage change, adoption, and governance post-launch - Establish monitoring, maintenance, and improvement processes
Topic 5: Support Responsible and Trustworthy AI Efforts	15%	- Establish ethical and governance frameworks - Manage bias, risk, compliance, and societal impact - Ensure fairness, transparency, accountability

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q295-Q300):

NEW QUESTION # 295
The project team at an IT services company is working on an AI-based customer support chatbot.
To help ensure the chatbot functions effectively, they need to define the required data. Which method meets the project requirements?

A. Gathering historical customer interaction logs for training data
B. Using synthetic data generated from sample customer conversations
C. Developing a new script based on anticipated customer queries
D. Integrating feedback from beta customers to refine the model

Answer: A

Explanation:
Gathering historical customer interaction logs provides real examples of customer questions, language patterns, issues, intents, and support responses. This helps define and supply the data needed to train an effective customer support chatbot.

NEW QUESTION # 296
Your team is testing the NLP model they just created to make sure it's performing as expected.
Some of your team members want to move this model to production and move to the next iteration.
What's wrong with this workflow?

A. Team members should not be able to move to new projects until senior management signs off
B. You need to make sure the AI Go/No Go questions have been addressed
C. Nothing is wrong with this workflow. You can move to the next iteration
D. Model Evaluation requires continuous model evaluation, retraining, and operationalization

Answer: B

NEW QUESTION # 297
You recently completed an image recognition project at your company that was focused on identifying different types of cars. You have now been assigned a new image recognition project that is focused on identifying different types of animals. You know you can shortcut model development by using a specific technique. What is this technique called?

A. Reinforcement Learning
B. Transfer Learning
C. Generative AI
D. Pre-Trained Models

Answer: B

Explanation:
Transfer Learning involves leveraging a model trained on one task (e.g., car recognition) and adapting it to a related task (e.g., animal recognition), significantly reducing development time and resources.

NEW QUESTION # 298
When looking to implement AI to help break the Digital Transformation logjam, it's important to:

A. Start with basic automation and introduce AI only as needed
B. Have the right culture for AI
C. Invest in technology solutions to solve the problem
D. Figure out which pattern(s) of AI are needed to incorporate intelligent systems into non-digital processes

Answer: B

NEW QUESTION # 299
You have been brought on to manage a recognition project, specifically an image recognition project, for an Autonomous Retail application. You know that you need to make sure you have sufficient data for this project. What's the best way to approach this?

A. Take inventory of all data your company has and use the relevant data
B. Take inventory of all data your team has and use the relevant data
C. Take all the data your company has as well as purchase additional external data
D. Take all the existing data you have and apply it to this project

Answer: A

Explanation:
Taking inventory of all company data and selecting relevant data ensures you use appropriate, high-quality datasets tailored to the project needs without unnecessary or irrelevant data.

NEW QUESTION # 300
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