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PMI CPMAI Practice Q&A's

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PMI CPMAI Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data for AI13%- DataOps concepts
- Data strategy and governance
- Data preparation and preprocessing
Topic 2: CPMAI Methodology41%- Phase III: Algorithm Selection & Model Training
  • 1. Oversee AI/ML model technique selection
  • 2. Manage model training and configuration
- Phase V: Operationalization
  • 1. Plan for deployment and integration
  • 2. Define success criteria and monitoring
- Phase II: Data Identification & Curation
  • 1. Identify data needs
  • 2. Assess data readiness and quality
- Phase VI: Iteration & Monitoring
  • 1. Retraining and model drift management
  • 2. Continuous monitoring and iteration
- Phase I: Problem Identification
  • 1. Identify business needs and solutions
  • 2. Evaluate initial AI feasibility
- Phase IV: Model Evaluation
  • 1. Evaluate model performance against metrics
  • 2. Oversee AI/ML model QA/QC
Topic 3: Machine Learning13%- Deep Learning and Neural Networks
- Supervised, Unsupervised, and Reinforcement Learning
- Algorithms and models (e.g., NLP, Computer Vision)
Topic 4: Managing AI8%- Managing AI project teams and resources
- Risk management in AI projects
- Stakeholder management
Topic 5: AI Fundamentals16%- Concepts and terminology of Artificial Intelligence
- Types of AI and Machine Learning
- AI capabilities and limitations
Topic 6: Trustworthy AI9%- Ethical considerations and bias
- Privacy and security
- Transparency and explainability

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

1. An insurance company is selecting an AI approach to automate simple claim approvals for low- risk cases. The organization wants the system to take actions with minimal human intervention based on predefined policies. Which AI capability best fits?

A) Hyperpersonalization
B) Predictive analytics
C) Autonomous systems
D) Conversational


2. An IT services company is developing an AI system to automate network security monitoring. The project manager needs to consider various factors to mitigate risks associated with false positives and false negatives. Which action should the project manager implement?

A) Operationalizing the nearest neighbor detection algorithms
B) Establishing a continuous feedback loop with security
C) Conducting model combinations and trade offs
D) Implementing a robust data security validation process


3. You're looking to take an image and have a Generative AI solution generate additional content beyond the bounds of the current image size. What Generative AI approach can you use?

A) Use of super-resolution to enhance the existing image
B) Use of inpainting to replace image components
C) Use of Generative Outpainting
D) Prompt engineering for new image generation


4. When looking to implement AI to help break the Digital Transformation logjam, it's important to:

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


5. Upper management is looking to roll out a new product and wants to see if there are any patterns and insights that can be discovered from customer data. Your team has been tasked to discover these potential patterns and structures within this data. Which type of machine learning approach would be most appropriate to pick for this problem?

A) Reinforcement Learning
B) All would work equally well
C) Unsupervised Learning
D) Supervised Learning


Solutions:

Question # 1
Answer: C
Question # 2
Answer: B
Question # 3
Answer: C
Question # 4
Answer: D
Question # 5
Answer: C

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