Databricks-ML-Pro › ML Ops

ML Ops Practice Questions

ML Ops on Databricks covers the lifecycle machinery around models: experiment tracking with MLflow, the Model Registry, deployment to Model Serving or batch jobs, and post-deployment monitoring. Questions are scenario-based, asking you to pick the right Databricks API, CLI command, or pattern to automate lineage, versioning, stage transitions, scaling, and retraining triggers.