数千人のPMI専門家で構成された権威ある制作チームが、CPMAI学習の質問を理解し、質の高い学習体験を楽しんでいます。試験概要と現在のポリシーの最近の変更に応じて、CPMAIテストガイドの内容を随時更新します。また、CPMAI試験の質問は、わかりにくい概念を簡素化して学習方法を最適化し、習熟度を高めるのに役立ちます。もう1つ、CPMAIテストガイドを使用すると、試験を受ける前に20〜30時間の練習でCognitive Project Management in AI (PMI-CPMAI)準備時間を短縮できることは間違いありません。
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: CPMAI Methodology | 41% | - Phase III: Algorithm Selection & Model Training
|
| Topic 2: AI Fundamentals | 16% | - AI capabilities and limitations - Concepts and terminology of Artificial Intelligence - Types of AI and Machine Learning |
| Topic 3: Data for AI | 13% | - Data strategy and governance - Data preparation and preprocessing - DataOps concepts |
| Topic 4: Trustworthy AI | 9% | - Transparency and explainability - Privacy and security - Ethical considerations and bias |
| Topic 5: Managing AI | 8% | - Risk management in AI projects - Managing AI project teams and resources - Stakeholder management |
| Topic 6: Machine Learning | 13% | - Supervised, Unsupervised, and Reinforcement Learning - Algorithms and models (e.g., NLP, Computer Vision) - Deep Learning and Neural Networks |
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質問 # 92
In preparation for an AI solution transition, the project team needs to ensure compliance with data regulations and ethical standards. They must identify and address potential privacy and transparency issues before moving forward.
What is the outcome if these requirements are neglected?
正解：C
解説：
Neglecting privacy, transparency, and regulatory requirements exposes the organization to noncompliance. This can result in legal action, fines, sanctions, and other regulatory penalties during or after the AI solution transition.
質問 # 93
When building your model you need to make sure you're not only checking for performance and making sure the model is giving the expected results. You also need to make sure the model is accomplishing the business objective.
At what phase of CPMAI is this most appropriate to do this?
正解：B
質問 # 94
An IT services company project manager is creating an AI project scope statement. They need to include details on the environments, devices, and personnel that will use the AI solution. What should the project manager do?
正解：A
解説：
Developing a comprehensive usage scenario analysis defines how the AI solution will be used, including the operating environments, devices, user roles, workflows, and personnel involved.
This provides the practical context needed for a complete AI project scope statement.
質問 # 95
An aerospace engineering firm is developing a machine learning model to predict component failures. The project manager needs help to ensure the training data is representative of real- world scenarios. Which method will meet the project manager's objective?
正解：C
解説：
PMI's CPMAI/PMI-CPMAI guidance emphasizes that, in the Data Understanding and Data Preparation phases, the team must identify appropriate datasets, evaluate training data requirements, validate "ground truth" quality, and explicitly assess data representativeness and potential bias issues before moving forward. Using historical data from multiple sources best supports representativeness because it increases coverage across operating conditions, environments, and failure modes that occur in real deployments (different fleets, sensors, maintenance practices, and duty cycles). This directly aligns with PMI's expectation that the project manager ensures readiness of data for model development through quality checks and representativeness assessments as part of go/no-go decisioning. In contrast, relying solely on synthetic data can reduce fidelity and distort real-world distributions if not carefully validated; competitor data often has ownership and fit-for-purpose limitations; and real-time monitoring is useful operationally but does not inherently make the training dataset representative. Therefore, aggregating and reconciling multi-source historical data is the most PMI-aligned method to meet the objective of representative training data prior to model development and evaluation.
質問 # 96
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?
正解：A
解説：
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.
質問 # 97
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