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Questions and Answers
Which step comes after Problem Identification in the AI Project Cycle?
Which step comes after Problem Identification in the AI Project Cycle?
- Data Modelling
- Problem Scoping (correct)
- Data Acquisition
- Data Exploration
What is the purpose of the AI Project Cycle?
What is the purpose of the AI Project Cycle?
- To identify problems in an organization
- To evaluate the success of an AI project
- To acquire data for AI projects
- To define the steps of an AI Project (correct)
Why is Problem Identification important in the AI Project Cycle?
Why is Problem Identification important in the AI Project Cycle?
- To define the problem accurately (correct)
- To make the problem more obvious
- To determine the tip of the iceberg problem
- To evaluate the success of the AI project
What is the first stage of the AI Project Cycle?
What is the first stage of the AI Project Cycle?
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What is the purpose of Data Modelling in the AI Project Cycle?
What is the purpose of Data Modelling in the AI Project Cycle?
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Study Notes
AI Project Cycle Overview
- The AI Project Cycle is a systematic approach to develop and implement AI projects.
Problem Identification
- The first stage of the AI Project Cycle is Problem Identification, which involves identifying and understanding the problem or opportunity to be addressed.
- Problem Identification is important in the AI Project Cycle because it sets the foundation for the entire project and ensures that the project addresses a real need or problem.
Data Modelling
- The purpose of Data Modelling in the AI Project Cycle is to develop and refine the data model to support the AI project.
Post-Problem Identification
- After Problem Identification, the next step in the AI Project Cycle is to define the project requirements and scope, which includes understanding the project goals, objectives, and constraints.
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