Mlops

How I would design the pipeline that moves a legacy database onto Azure: bulk load and CDC, a medallion lakehouse with a quality gate that actually stops things, star schemas and SCD2, a feature store, and the security, monitoring and cutover plan around it.

A conceptual guide to MLOps tooling — MLflow, artifact versioning, reproducible pipelines, framework integrations, alternatives, and deploying and improving models in production.

ML engineer prep: Python infra, NumPy, PyTorch, distributed training, scientific formats, MLflow, and common coding patterns.