Free PMI Certified Professional in Managing AI Exam PMI-CPMAI Exam Practice Test

During the evaluation of an AI solution, the project team notices an unexpected decline in model performance. The model was previously achieving high accuracy but has recently shown increased error rates.Which action will identify the cause of the performance decline?

• Reviewing recent changes made to the model's architecture and parameters
• Checking for issues in the data preprocessing pipeline that may have introduced noise
• Increasing the amount of regularization to prevent overfitting
• Analyzing the distribution of real world data for potential shifts

A telecommunications company is preparing data for an AI tool. The project team needs to ensure the data is in the right shape and format for model training. In addition, they are working with a mix of structured and unstructured data.Which method will address the project team's objectives?

• Converting unstructured data into structured formats
• Employing a data transformation tool to standardize formats
• Using a hybrid storage system for both data types
• Separating structured and unstructured data into different databases

A hospital system has been using a chatbot and has received complaints from end users. The end users believe they are speaking to a person but are frustrated when answers do not make sense.To help ensure end users know that they are engaging with an AI chatbot, what should be considered to support transparency?

• Inclusion of diverse data sets
• Operationalize advanced algorithms
• Disclosure notice with each use
• Use of interpretable AI models

A government agency is implementing an AI-powered tool to enhance data security through anomaly detection. The project manager is assembling the team. To identify the subject matter experts (SMEs) who can provide the best insights and contributions to this project, the project manager needs to consider their experience and expertise in various technical domains.Which method will help identify the qualified data SMEs?

• Conducting interviews to assess their knowledge in anomaly detection
• Examining their expertise in neural network calibration and hyperparameter tuning
• Assessing proficiency in developing generative adversarial networks (GANs) and experience in successfully generating synthetic data
• Evaluating expertise with existing data architectures and their ability to optimize databases

A government project plans to implement an AI-based fraud detection system and the project team needs to define the success criteria. They identified potential improvements in detection accuracy, reduction in investigation time, and cost savings as key performance indicators (KPIs). However, they are unsure how to effectively quantify these KPIs.Which two approaches should be used? (Choose 2)

• Rely on only qualitative feedback from stakeholders
• Implement a continuous performance monitoring system
• Use random benchmarks without industry comparison
• Establish a baseline using historical data comparisons
• Set fixed performance targets based on theoretical models

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

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

A financial services firm is integrating AI to enhance fraud detection. To oversee data evaluation, the project manager needs to ensure the integrity and accuracy of input data, including transaction histories and customer profiles.Which method provides the results that address the requirements?

• Using a fact checklist to systematically verify data sources
• Implementing alternative approaches to process data differently
• Applying a visualization generator to create data flow diagrams

A company's leadership team has requested insights into the AI model's ability to support decision-making processes without requiring them to understand complex technical details.Which step should the project manager take?

• Explain the role of neural network architectures in prediction accuracy
• Describe the model's backpropagation and gradient descent optimization
• Discuss how ensemble methods improve the model's robustness
• Demonstrate how the model's output can be integrated and used in end-user systems

A project team is trying to determine the most suitable environment to operationalize their AI/machine learning (ML) solution. They need to consider various factors to help ensure a successful implementation.What should the project manager do?

• Consider the cost of implementation
• Identify the end users and their interactions
• Analyze the solution's compliance requirements

A team needs to identify which parts of the project they are working on will require AI and which will not. In addition, they need to determine technology and data requirements.Which method should be used?

• Technical feasibility assessment
• Components-based analysis