Your question is Model Versioning and Monitoring. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Describe the process of model versioning and monitoring in an AI project.
Explain how you would version training data, source code, model artifacts, configurations, and dependencies, then promote models through development, staging, and production. Cover deployment tracking, prediction quality, data drift, model drift, latency, failures, rollback, alerting, and retraining triggers.
