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Data Engineering is 80%+ of most AI projects, so building a good Data Engineering Environment is key to AI Project Success. As the manager of this project, you need to make sure you have correct staffing needs.

What’s the most critical role to staff for in the Big Data / Data Engineering Environment?

A.

Data Scientists

B.

Data Engineering and Data Scientists

C.

Senior management

D.

Data Engineering

E.

All roles are critical to staff in the Four different AI Tech environments

Your team is looking to develop an RPA bot to help assist call center agents while on providing support. What type of bot should your team be creating?

A.

Augmented Intelligence

B.

Attended bot

C.

RPA is not the right solution to this problem

D.

Unattended bot

Your team is working on an AI system to provide a more personalized experience for customers on your website. What should the team do in regard to determining the pattern of AI with regards to the ROI of the project?

A.

First identify the AI pattern you want to use and then figure out the ROI

B.

First determine the pattern of AI you want to use and then work with stakeholders to come up with ROI

C.

First identify the objective you’re trying to solve or the ROI you desire and then use that to figure out the correct pattern

D.

First talk to senior managers who set the ROI of the project

Your team is working on an image recognition project, have collected the appropriate data for the project, and have picked a neural network algorithm. They are now ready to train their model.

In which phase of CPMAI is this done?

A.

Phase I

B.

Phase II

C.

Phase III

D.

Phase IV

E.

Phase V

F.

Phase VI

During CPMAI Phase IV: Model Development, which of the following is not done during this phase?

A.

Algorithm Selection

B.

Model training

C.

Model tuning

D.

Model Selection

Senior management has tasked your group to analyze a data set to uncover insights into the data. What is the best approach to use to do this?

A.

Data Governance

B.

Data Integration

C.

Data preparation

D.

Data Mining or Data Analytics

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

Your team is working on a new facial recognition application. Since this technology has the potential to be mis-used you think it’s important to set guidelines for the proper use of this application and you want to make sure the AI system is built for some positive purpose. What area of Trustworthy AI does this best fall under?

A.

Transparent AI

B.

Governed AI

C.

Responsible AI

D.

Explainable AI

Your company is insisting on running an automation project and applying AI best practices and methodologies to the project. You understand that automating things is just the act of using machines to repeat tasks, and does not require AI to achieve results. You think it is overkill but the project moves forward as planned.

What would likely have helped avoid this conflict?

A.

Nothing – running automation projects like autonomous projects is the correct thing to do.

B.

Everyone on the team should understand the differences between automation and autonomous systems.

C.

Senior management should become involved in the project.

D.

Applying a hybrid approach of automation and AI best practices would have achieved better results.

Use cognitive technologies/AI when you can’t code the rules or you can’t scale easily with people or automation. As a good rule of thumb when deciding if AI is right for the project you should:

A.

Decide if it’s a statistics pattern. If it’s statistical then go with the AI project.

B.

Decide if it’s probabilistic or deterministic patterns. If it’s deterministic then go with the AI project.

C.

See if simple rules work. If yes, then pick the right AI solution to solve the problem.

D.

Decide if it’s probabilistic or deterministic patterns. If it’s probabilistic then go with the AI project.