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PMI CPMAI Exam Syllabus Topics:

Section	Weight	Objectives
AI Fundamentals	16%	- Concepts and terminology of Artificial Intelligence - Types of AI and Machine Learning - AI capabilities and limitations
Machine Learning	13%	- Deep Learning and Neural Networks - Algorithms and models (e.g., NLP, Computer Vision) - Supervised, Unsupervised, and Reinforcement Learning
CPMAI Methodology	41%	- Phase IV: Model Evaluation 1. Evaluate model performance against metrics 2. Oversee AI/ML model QA/QC - Phase II: Data Identification & Curation 1. Assess data readiness and quality 2. Identify data needs - Phase III: Algorithm Selection & Model Training 1. Manage model training and configuration 2. Oversee AI/ML model technique selection - Phase VI: Iteration & Monitoring 1. Retraining and model drift management 2. Continuous monitoring and iteration - Phase I: Problem Identification 1. Evaluate initial AI feasibility 2. Identify business needs and solutions - Phase V: Operationalization 1. Plan for deployment and integration 2. Define success criteria and monitoring
Managing AI	8%	- Managing AI project teams and resources - Stakeholder management - Risk management in AI projects
Data for AI	13%	- Data preparation and preprocessing - Data strategy and governance - DataOps concepts
Trustworthy AI	9%	- Ethical considerations and bias - Privacy and security - Transparency and explainability

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q115-Q120):

NEW QUESTION # 115
You have an Anomaly Detection project you're working on and you need a simple approach of clustering data into classified groups. Which algorithm is the best choice given this situation?

A. K-Means Clustering
B. Hidden Markov Model
C. Neural Network
D. Decision Tree

Answer: A

Explanation:
K-Means clustering is a straightforward and widely used algorithm for grouping data into clusters, suitable for anomaly detection tasks that require classification into groups.

NEW QUESTION # 116
You're working with a small inexperienced team on a new ML project. Choosing the best algorithm with the best settings given the training and test data is proving to be very hard for them. You lack the critical data science resources available on your team, and can't wait weeks until a data science resource becomes available to join your team. What's your best course of action?

A. Find a citizen data scientist to help
B. Put the project on hold until the resources needed become available
C. Use an AutoML solution
D. Outsource the project ASAP

Answer: C

Explanation:
AutoML tools automate algorithm selection and hyperparameter tuning, enabling less experienced teams to develop models efficiently without waiting for specialized data science resources.

NEW QUESTION # 117
The growth of Big Data has led to a desire to be able to do more to process and extract more value from Big Data. Simply storing data and providing analytics is no longer enough anymore to remain competitive.
To keep your organization competitive, you need to:

A. Make sure all senior leadership is data literate, understands the Vs of big data, data's connections to your specific team, and how to extract value from big data to unleash it for competitive advantage.
B. Make sure senior management has deep understanding of big data and how best to extract value from big data to unleash it for competitive advantage.
C. Make sure everyone on the team has an understanding of data, its connections to the organization, and how to extract value from big data to unleash it for competitive advantage.
D. Make sure the technical team has deep understanding of big data and how best to extract value from big data to unleash it for competitive advantage.

Answer: A

NEW QUESTION # 118
Your team is working on an image recognition project, have collected the appropriate data for the project, and have picked a neural network algorithm. They are now ready to train their model. In which phase of CPMAI is this done?

A. Phase I
B. Phase VI
C. Phase II
D. Phase III
E. Phase V
F. Phase IV

Answer: F

Explanation:
Phase IV of CPMAI is where model training and development occur, including training chosen algorithms like neural networks on prepared data.

NEW QUESTION # 119
You have an Anomaly Detection project you're working on and you need a simple approach of clustering data into classified groups. Which algorithm is the best choice given this situation?

A. K-Means Clustering
B. Hidden Markov Model
C. Neural Network
D. Decision Tree

Answer: A

NEW QUESTION # 120
......

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