The AI project life-cycle typically comprises three principal phases: Project Scoping, Design or Build, and Production Deployment.
Project Scoping defines the problem, establishes objectives, and details deliverables.
The Design or Build phase encompasses data collection, model creation, training, and validation.
Production Deployment involves integrating the AI solution into operational environments and overseeing its performance.
Data visualization, conversely, is a method applied across different stages, particularly during data analysis and reporting.
It serves as a supportive function for interpreting and conveying data insights, rather than a distinct phase.
Consequently, option (B) is accurate: Data visualization is not among the three core stages.