CPMAI Practice Mock - CPMAI Passguide

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PMI CPMAI Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data for AI	13%	- DataOps concepts - Data preparation and preprocessing - Data strategy and governance
Topic 2: Managing AI	8%	- Stakeholder management - Managing AI project teams and resources - Risk management in AI projects
Topic 3: Trustworthy AI	9%	- Transparency and explainability - Privacy and security - Ethical considerations and bias
Topic 4: AI Fundamentals	16%	- Types of AI and Machine Learning - Concepts and terminology of Artificial Intelligence - AI capabilities and limitations
Topic 5: Machine Learning	13%	- Supervised, Unsupervised, and Reinforcement Learning - Deep Learning and Neural Networks - Algorithms and models (e.g., NLP, Computer Vision)
Topic 6: CPMAI Methodology	41%	- Phase V: Operationalization 1. Plan for deployment and integration 2. Define success criteria and monitoring - Phase IV: Model Evaluation 1. Oversee AI/ML model QA/QC 2. Evaluate model performance against metrics - Phase I: Problem Identification 1. Evaluate initial AI feasibility 2. Identify business needs and solutions - Phase III: Algorithm Selection & Model Training 1. Manage model training and configuration 2. Oversee AI/ML model technique selection - Phase II: Data Identification & Curation 1. Assess data readiness and quality 2. Identify data needs - Phase VI: Iteration & Monitoring 1. Continuous monitoring and iteration 2. Retraining and model drift management

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q274-Q279):

NEW QUESTION # 274
An organization is planning to use AI for real-time auctions and bidding. Which AI capability should be implemented to meet the organization's objectives?

A. Recognition systems
B. Autonomous systems
C. Predictive analytics
D. Goal-driven systems

Answer: B

Explanation:
Autonomous systems can independently make decisions and take actions in dynamic, rapidly changing environments. For real-time auctions and bidding, they can continuously evaluate conditions, adjust bids, and execute bidding decisions without requiring constant human intervention.

NEW QUESTION # 275
You're working on a computer vision application and realize that you do not have enough real world data for the project. You need additional data created to support your training needs.
Specifically, the images you need are of people in different poses. What is the best way to obtain this data?

A. Make use of Synthetic Training Data
B. Make use of this data from surveillance footage
C. Make use of this data by having employees pose in the positions required
D. Make use of data from different departments

Answer: A

NEW QUESTION # 276
During the business understanding phase, the project manager realizes that the project team has overlooked requirements for the AI model. The model should have a high level of explainability and transparency. What should the project manager do?

A. Develop an algorithm to account for future model adjustments.
B. Define a process for data aggregation and analysis.
C. Revisit the training data for the smart algorithm.
D. Ensure data compliance requirements are clearly documented.

Answer: D

Explanation:
Clearly documenting compliance requirements helps ensure explainability and transparency expectations are formally captured during business understanding. This guides later model selection, validation, governance, and stakeholder review so the AI system can meet accountability and regulatory expectations.

NEW QUESTION # 277
A logistics company is operationalizing an AI system to improve delivery times. The project team needs to identify performance constraints that may impact the AI solution. Which method should the project manager use to meet the team's objective?

A. Training employees on AI ethics
B. Implementing advanced data visualization tools
C. Conducting a preliminary feasibility study
D. Benchmarking against competitors

Answer: C

Explanation:
Conducting a preliminary feasibility study helps identify performance constraints such as data availability, processing capacity, integration limits, latency, scalability, and operational readiness before the AI delivery-time optimization system is fully implemented.

NEW QUESTION # 278
The team is working to build a data preparation pipeline for the conversational chatbot project.
Which phase of CPMAI is this done?

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

Answer: B

NEW QUESTION # 279
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