An e-commerce company wants to build a recommendation system. The data is stored in a cloud data warehouse. The team needs to experiment with different algorithms quickly and then deploy the best model as a real-time API. Which tool selection best matches the project phases?

Use a spreadsheet to train the model and export it as a file.

Use a cloud notebook service for experimentation and a managed model serving platform for deployment.

Use a data visualization tool to build the model.

Use a local Jupyter notebook and a manual Flask server for deployment.

A non-profit organization wants to analyze text data to identify trends in public feedback. They have a small budget and volunteers with basic Python skills. The data is stored in CSV files. Which tool selection is most appropriate for this project?

Use a commercial big-data platform with a large cluster.

Use a cloud-based AutoML service with a complex pipeline.

Use a deep learning framework to build a custom model from scratch.

Use an open-source Python library for text processing and a simple script for analysis.

A non-profit organization with a very limited budget is building a text-classification model to categorize public documents. They have a small team of volunteers with moderate Python skills. They need to deploy the model on their own low-cost server. Which tool choice is most appropriate?

Use a cloud-based ML service that offers a free tier, but plan to scale up to a paid plan immediately.

Build a custom deep learning model from scratch using a low-level framework, without using any pre-built libraries.

Use an open-source ML library such as scikit-learn, and deploy the model as a simple web service on the server.

Purchase a commercial AutoML platform that requires no coding and includes hosting.

A logistics company is developing an AI model to optimize delivery routes. The team has already collected GPS and traffic data. They are now in the model-building phase and need to experiment with different algorithms quickly. Later, they will deploy the model to a mobile app used by drivers. Which tool choice best supports the current phase while also considering future deployment?

Deploy a preliminary model directly to the mobile app now, then continue training it in production.

Use a notebook environment with an ML framework for rapid experimentation, and plan to wrap the final model in a REST API for the mobile app.

Select a commercial ML platform that automates model building, but do not consider how the model will be served to the app.

Use a data visualization tool to explore the GPS data, then manually code the routing logic in the mobile app.

EC-CouncilArtificial Intelligence Essentials

Domain 3Objective 6

Tool Selection Based on AI Project Requirements AIE Practice Questions (Page 2)

Part of the Building Blocks of AI domain, which makes up ~25% of our current practice bank.

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Questions 6–10

6application · medium
An e-commerce company wants to build a recommendation system. The data is stored in a cloud data warehouse. The team needs to experiment with different algorithms quickly and then deploy the best model as a real-time API. Which tool selection best matches the project phases?
Select an answer first
7application · medium
A non-profit organization wants to analyze text data to identify trends in public feedback. They have a small budget and volunteers with basic Python skills. The data is stored in CSV files. Which tool selection is most appropriate for this project?
Select an answer first
8application · medium
A non-profit organization with a very limited budget is building a text-classification model to categorize public documents. They have a small team of volunteers with moderate Python skills. They need to deploy the model on their own low-cost server. Which tool choice is most appropriate?
Select an answer first
9application · medium
A logistics company is developing an AI model to optimize delivery routes. The team has already collected GPS and traffic data. They are now in the model-building phase and need to experiment with different algorithms quickly. Later, they will deploy the model to a mobile app used by drivers. Which tool choice best supports the current phase while also considering future deployment?
Select an answer first
10foundation · easy
A team is evaluating an AI tool that supports standard data formats like CSV and JSON and provides APIs for connecting to their existing data pipeline. Which aspect of the tool are they assessing?
Select an answer first

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Tool Selection Based on AI Project Requirements AIE Practice Questions (Page 2)

Questions 6–10

An e-commerce company wants to build a recommendation system. The data is stored in a cloud data warehouse. The team needs to experiment with different algorithms quickly and then deploy the best model as a real-time API. Which tool selection best matches the project phases?

A non-profit organization wants to analyze text data to identify trends in public feedback. They have a small budget and volunteers with basic Python skills. The data is stored in CSV files. Which tool selection is most appropriate for this project?

A non-profit organization with a very limited budget is building a text-classification model to categorize public documents. They have a small team of volunteers with moderate Python skills. They need to deploy the model on their own low-cost server. Which tool choice is most appropriate?

A team is evaluating an AI tool that supports standard data formats like CSV and JSON and provides APIs for connecting to their existing data pipeline. Which aspect of the tool are they assessing?

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