PMI-CPMAI試験無料問題集（161題）「PMI Certified Professional in Managing AI 認定」

出題：1

A project team is using a prompt engineering approach to improve AI/machine learning (ML) model outputs.
They started with broad questions and then narrowed down the specific elements. If the team had provided insufficient context, what would be the result?

A. The output would include higher accuracy.

B. The model would perform more efficiently.

C. The model would generate more creative outputs.

D. The responses would lack relevance.

正解：D 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：2

An insurance company is in the Business Understanding phase of an AI project to develop a chatbot that provides personalized assistance to customers.
The chatbot will include tailored policy recommendations and claim support based on individual customer data.
The project manager needs to choose an appropriate technical performance benchmark for the project.
What should the project manager select?

A. The chatbot ' s rate of successful self-service resolution without needing agent escalation.

B. The chatbot ' s ability to access the customer policy information needed for personalized suggestions.

C. The chatbot ' s ability to suggest policies with a personalized relevance score above a chosen threshold.

D. The chatbot ' s 1% increase in customer acquisition for new products after one year of use.

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：3

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. Autonomous systems

B. Predictive analytics

C. Hyperpersonalization

D. Conversational

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：4

A project team at a healthcare provider is determining whether their patient records are adequate for an AI diagnostic tool. They need to validate that the data covers a broad spectrum of conditions and demographics.
What is an effective method to assure data suitability?

A. Performing demographic analysis and stratifying patient data

B. Analyzing data variance and ensuring balanced sampling

C. Conducting a cross-sectional study on data diversity

D. Implementing a longitudinal data-gathering approach

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：5

A capital markets firm is exploring the use of AI to enhance its trading algorithms. The firm expects the AI solution will increase trading accuracy and profitability. The project manager needs to create a business case to justify the AI investment.
Which method will provide results that meet the firm ' s goals and objectives?

A. Developing a financial impact assessment

B. Conducting a market trend analysis

C. Consulting with AI vendors

D. Performing a scenario analysis

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：6

An AI project team has prepared the data and is ready to proceed with model development.
Which action should the project manager perform next?

A. Document the performance metrics for the model

B. Ensure go/no-go questions have well-defined answers

C. Conduct a final assessment of the data quality

D. Prepare a report on the model ' s scalability

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：7

A government agency is operationalizing an AI system to optimize urban traffic flow that changes unexpectedly. The project manager needs to gather the required data from traffic cameras, sensors, and historical traffic patterns. What is an effective technique to meet the project manager's goals?

A. Applying dimensionality reduction to manage the complexity of traffic sensor data

B. Utilizing data augmentation to increase the diversity of traffic scenarios

C. Developing a probabilistic graphical model to infer latent traffic scenarios

D. Implementing real-time data synchronization to ensure up-to-date traffic analysis

正解：D 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：8

A project involves integrating AI systems across multiple departments, each with different access levels. This complex AI project has presented the project manager with significant issues related to data misuse. The project team has been focused on their ethics guidelines but continues to experience data misuse. The project involves different regional data protection regulations which further increases the complexity.
What issue will cause these challenges to occur?

A. Lack of a detailed plan addressing a governance strategy

B. Limited awareness of explainability requirements

C. Failure to implement robust encryption for data security

D. Overlooking algorithmic bias and fairness concerns

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：9

A project team is using a generative AI assistant to draft stakeholder communications. The drafts are often generic and miss project constraints. What is the most likely cause?

A. The model is too efficient

B. The tool requires more compute

C. The team is over-monitoring outputs

D. The prompts provide insufficient context and constraints

正解：D 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：10

An aerospace company is evaluating whether their sensor data meets the requirements for an AI-based predictive maintenance system. The project team needs to ensure that the data ' s accuracy, resolution, and timeliness are adequate to predict equipment failures.
Which method addresses the requirements?

A. Implementing a data governance framework to ensure compliance

B. Analyzing data completeness and conducting feature engineering

C. Evaluating the data schema and integrating additional data sources

D. Performing a data quality assessment focusing on precision and latency

正解：D 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：11

A manufacturing firm plans to use AI to predict equipment failures. The team can access sensor data but it contains many missing values and out-of-range readings. What should the project manager prioritize first?

A. Deploy the model quickly and fix issues later

B. Ignore the sensor data and use only expert opinion

C. Focus only on UI design for the dashboard

D. Data understanding and quality assessment to characterize missingness and anomalies

正解：D 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：12

After completing an AI project, the project manager begins preparing the final report and reflecting on lessons learned. They identified that the project team lacked sufficient AI and data knowledge.
If adequate knowledge was available, how would the result be different?

A. The AI project team would have required less external consultation.

B. The AI project would have faced fewer governance issues.

C. The AI model would have achieved higher accuracy rates.

D. The AI project timeline would have been shorter.

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：13

A manufacturing company is implementing an AI system to optimize production schedules. The project manager needs to gather the required data from machine sensors, production logs, and supply chain databases.
During data collection, they notice discrepancies in machine sensor data.
What should the project manager do first?

A. Develop a data integration framework to harmonize formats.

B. Implement a robust data validation and correction process.

C. Outsource data preprocessing to an external vendor.

D. Replace machine sensors for real-time data accuracy.

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：14

An organization is considering deploying an AI solution to automate a repetitive and mundane task that is currently performed by employees. They need to ensure that the AI solution is scalable and can handle increasing volumes of work without becoming too complex to manage.
Which method will help to ensure scalability?

A. Implementing a rule-based approach with extensive manual updates

B. Utilizing a traditional software solution with regular performance monitoring

C. Developing a cognitive solution using natural language processing

D. Establishing a semiautomated process combining AI and human oversight

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

PMI-CPMAI試験無料問題集「PMI Certified Professional in Managing AI 認定」