CPMAI_v7 試験問題を無料オンラインアクセス

Your team was given a large dataset and has been tasked with organizing the data by type to make better insights from the results. You are facing problems with the approach that the previous project lead used which was a regression algorithm.
What type of algorithm is the best approach for this project?

• A.Binary (or Binomial) Classification
• B.Regression
• C.Clustering
• D.Multiclass Classification

In the case that an algorithm you want to use isn't algorithmically explainable, AI systems should try to do the following:

• A.Provide a means to have a different team on the project
• B.Provide a means to have contestability of the algorithm selected
• C.Provide a means to interpret AI results so that cause and effect can be represented.
• D.Provide a means to reverse-engineer the algorithm to inspect its performance

You have been brought on to manage a recognition project, specifically an image recognition project, for an Autonomous Retail application. You know that you need to make sure you have sufficient data for this project. What's the best way to approach this?

• A.Take inventory of all data your company has and use the relevant data
• B.Take inventory of all data your team has and use the relevant data
• C.Take all the existing data you have and apply it to this project
• D.Take all the data your company has as well as purchase additional external data

You're creating an AI-enabled chatbot that is going to access user data. What areas related to data governance do you need to make sure you're addressing? (Select all that apply.)

• A.Security Risks
• B.Data Quantity Issues
• C.Data Sharing challenges
• D.Change Management Issues
• E.Data Quality Issues
• F.Privacy Risks
• G.Business Risks

For AI projects the code and systems don't matter as much as the data. In fact, big data is what's powering much of this latest wave of AI. What's most important for your company to consider around data?

• A.Have team members that have experience, understanding of tools, and the ability to deal with massive volumes of data.
• B.Collect enormous amounts of data - the more data the better.
• C.Because of almost-infinite storage and compute power, collect as much data as possible and deal with organizing it later.
• D.Understanding which algorithms are best for your data needs.