Your organization wants to keep an eye on AI systems for Governance purposes. What are the most crucial things to consider? (Select all that apply.)

• A.Vendor procurement methods
• B.AI System testing requirements
• C.Continuous System monitoring
• D.Data source identification
• E.Algorithm selection
• F.Human chain of accountability
• G.Key Performance Indicators (KPIs)
• H.ROI determination

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Which of the following best describes the technical definition of Machine Learning?

• A.An approach to using increasing levels of intelligence to solve greater cognitive needs from unintelligent automation to autonomous business process.
• B.A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.
• C.The application of pre-defined rules and algorithms to solve complex problems.
• D.The use of computing technology to enable machines to gain cognitive intelligence.

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You're working on a project and are working with personally identifiable information (PII). What's the best approach to take when it comes to collecting and using this data?

• A.Use noise reduction techniques to reduce all forms of data noise
• B.Implement a new data privacy policy
• C.Store the data in a data warehouse
• D.If this data is not needed, use Data anonymization techniques to remove it before feeding to models

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You are leading a project to develop a new predictive maintenance solution. Together with your project team you determine your data needs, see if you have access to the data, and then begin working on the project.
Which phase best describes the work you are performing?

• A.Phase I
• B.Phase II
• C.Phase III
• D.Phase IV
• E.Phase V
• F.Phase VI

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You're working with an inexperienced team and this is all their first AI project. You're trying to work on a supervised learning binary classification problem to determine if emails are spam or not.
What is the best approach for this project?

• A.Pick a simple algorithm such as naive bayes
• B.Pick a neural network algorithm since you know this works well for supervised learning approaches
• C.Pick an ensemble method since you're not sure which algorithm will perform best
• D.Pick a simple algorithm such as Gaussian mixture

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