PMI-CPMAI 무료 덤프문제 온라인 액세스

An AI project team with a manufacturing company needs to ensure data integrity before moving to model development. They discovered some data inconsistencies due to manual entry errors.
What is an effective method that helps to ensure data integrity?

• A.Using machine learning algorithms to detect and correct errors
• B.Automating data entry processes
• C.Implementing real-time data validation rules
• D.Conducting regular audits of manually entered data

A healthcare provider had physicians review a potential diagnostic AI application. During their final review, the project team, along with the physicians, discovered that the AI model exhibits a higher than acceptable false-positive rate.
Before making the go/no-go AI decision, which next step should be performed by the team?

• A.Reevaluate the business objectives and outcomes
• B.Focus on the model's ethical implications
• C.Increase the training data volume
• D.Adjust the hyperparameters for better generalization

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.Conduct a final assessment of the data quality
• B.Document the performance metrics for the model
• C.Ensure go/no-go questions have well-defined answers
• D.Prepare a report on the model's scalability

An aerospace firm is developing an AI system for predictive maintenance of their aircraft. The project team needs to define the required data to train the model.
Which activity should the project manager implement?

• A.Implementing data cleaning and preprocessing routines
• B.Conducting a pilot test with a small dataset
• C.Developing a comprehensive data collection strategy
• D.Setting up real-time data streaming from aircraft sensors

A project team is preparing to move to the next phase of their AI project. The team needs to ensure that all transparency and explainability requirements are met.
Which activity should the project team perform?

• A.Establish a feedback mechanism for ongoing evaluation
• B.Conduct a thorough data quality assessment
• C.Document the decision-making process of the AI model
• D.Define the ethical guidelines for the AI project