Question 1

Your team has collected petabytes of data for your AI project. As the project lead, you understand this is too much data to use for this iteration of the project. What is the best course of action to take with this data?

Options :

A : Data selection and attribute pruning to reduce overall size and data complexity.

B : Data Deduping to reduce overall size and data complexity.

C : Data integration focused on reducing the number of data sources.

D : Careful algorithm selection that reduces the need for data.

Answer: A

Question 2

An inexperienced team is training a neural network model on a desktop computer and this is taking a significant amount of time. What would you recommend to them to speed up model training?

Options :

A : Train the model over multiple desktop computers

B : Train the model on GPUs

C : Use a contractor to do the training portion

D : Break the dataset up into multiple smaller datasets and train the model on each of the smaller datasets over a desktop computer

Answer: B

Question 3

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?

Options :

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

Answer: D

Question 4

During which phase of an AI project should you consider Trustworthy AI considerations?

Options :

A : Phase I: Business Understanding

B : Phase II: Data Understanding

C : Phase VI: Model Operationalization

D : Every Phase of the AI project

Answer: D

Question 5

Your team is running a simulation-based optimization exercise to increase routing efficiency. Learning for this exercise is done through "trial and error". Which type of machine learning approach is being leveraged for this exercise?

Options :

A : Unsupervised Learning

B : Reinforcement Learning

C : Supervised Learning

D : All would work equally well

Answer: B

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