A project manager needs to select an effective technique to address distinct outputs and objectives in AI/machine learning (ML) model training. What should the project manager use?

• A.A generic prompt template
• B.A sequence of prompts tailored to each output
• C.A single comprehensive prompt for all tasks
• D.A fixed set of predefined prompts

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The confusion matrix measures how the algorithm performs for a binary classification activity. As your team is running tests to evaluate model performance, they are seeing the model is incorrectly categorizing flowers as trees. Your model is provided the following:

• A.False Negative results
• B.False Positive results
• C.True Positive results
• D.True Negative results

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Your team is running a forecasting project and wants to use previous user data to better predict future outcomes. However your team doesn't have access to all the data it needs.
What's the best course of action?

• A.Do not move forward until you have access to all the data you need.
• B.Move ahead as planned and hope you get access to the data once you need it. Since you're using an iterative approach you can always go back to steps as needed later on.
• C.Move ahead as planned so you stay on time with your project.
• D.Cautiously move forward knowing you may need to pause mid-project which is ok.

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Recently, you implemented an augmented intelligence application at work to help employees do their job better. However, employees have been resistant to this change and aren't using the application as expected.
What could have been done better to get the team to feel comfortable with this technology and use it? (Select all that apply.)

• A.Have upper management relay to employees this tool is to augment, and not replace their jobs.
• B.Provide training for everyone to have all employees feel more comfortable using the technology even if they aren't using the technology yet.
• C.Ask end users what information and technology they need to help them do their job better and build the tool to help with these pain points.
• D.Have the team that built the technology to relay to employees this tool is to augment, and not replace their jobs.

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Your team is working on a new loan decision model that takes a number of factors and data points into consideration and then automatically approves or denies a loan. After a month in operation someone does a review and notices that the system is denying a large number of loans from a certain demographic when all other factors from people in other regions (such as age, salary, and credit score) are the same. What is most likely happening here?

• A.Data privacy issues leading to data sharing concerns
• B.Biased data sets leading to algorithmic discrimination
• C.Generative AI models hallucinating data results
• D.Nothing is wrong, algorithmic decisions will never be 100%

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