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CS Professional · Artificial Intelligence, Data Analytics and Cyber Security - Laws and Practice · Artificial Intelligence - Introduction and Basics

In the typical AI project lifecycle, which sequence correctly orders the stages?

The correct order is problem definition, then data collection and preparation, then model training and evaluation, and finally deployment with ongoing monitoring. A model cannot be trained before data exists, and it should not be deployed before it is evaluated.

  1. AModel training, data collection, problem definition, deployment
  2. BProblem definition, data collection and preparation, model training and evaluation, deployment and monitoringCorrect
  3. CDeployment, data collection, problem definition, model training
  4. DData collection, deployment, model training, problem definition

Explanation

A project begins by defining the problem, then gathers and prepares data, trains and evaluates the model, and finally deploys it and monitors it. Training cannot precede data collection, and deployment comes only after evaluation. Monitoring continues after deployment to catch drift.

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