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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: CPMAI Methodology | 41% | - Phase I: Problem Identification
|
| Topic 2: AI Fundamentals | 16% | - Concepts and terminology of Artificial Intelligence - AI capabilities and limitations - Types of AI and Machine Learning |
| Topic 3: Trustworthy AI | 9% | - Ethical considerations and bias - Transparency and explainability - Privacy and security |
| Topic 4: Data for AI | 13% | - DataOps concepts - Data preparation and preprocessing - Data strategy and governance |
| Topic 5: Managing AI | 8% | - Stakeholder management - Managing AI project teams and resources - Risk management in AI projects |
| Topic 6: Machine Learning | 13% | - Deep Learning and Neural Networks - Algorithms and models (e.g., NLP, Computer Vision) - Supervised, Unsupervised, and Reinforcement Learning |
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NEW QUESTION # 259
Multiple teams are developing AI solutions independently, resulting in inconsistent ethical practices and governance standards. Leadership wants to ensure alignment across all projects.
What is the best action for the project manager to recommend?
Answer: C
Explanation:
Governance frameworks ensure consistent ethical and operational standards.
NEW QUESTION # 260
An IT services company is integrating an AI solution to automate its customer service functions.
The integration team is facing resistance from the customer's employees.
Which action should the project manager perform to manage this risk?
Answer: C
NEW QUESTION # 261
A project charter states that the AI solution will "significantly improve customer experience." What is the deficiency in this statement?
Answer: B
Explanation:
Success criteria must be specific and measurable so that model evaluation can determine objectively whether the business objective is met. Qualitative statements provide no threshold against which results can be assessed at phase gates.
NEW QUESTION # 262
A telecommunications company is considering an AI solution to improve customer service through automated chatbots. The project team is assessing the feasibility of the AI solution by examining its potential scalability and effectiveness.
What will present the highest risk to the company?
Answer: A
Explanation:
Breaching customer data privacy regulations creates the most significant organizational risk because it can lead to legal penalties, regulatory sanctions, reputational damage, and loss of customer trust. Unlike capacity, skills, or integration issues - which are technical problems that can be remediated within the project - a privacy violation has irreversible consequences that extend beyond the project to the entire company. Privacy compliance must therefore be a primary consideration when assessing an AI chatbot solution in a regulated industry.
NEW QUESTION # 263
Data Engineering is 80%+ of most AI projects, so building a good Data Engineering Environment is key to AI Project Success. As the manager of this project, you need to make sure you have correct staffing needs.
What's the most critical role to staff for in the Big Data / Data Engineering Environment?
Answer: D
NEW QUESTION # 264
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