A staff-level tour of the data and ML engineering stack — warehouse modeling, batch and streaming pipelines, data quality, feature stores, training and evaluation, deployment, drift monitoring, and production RAG — taught through mechanisms, real tools, and the dollar-and-latency consequence of getting each one wrong.
That's what makes passing it mean something. Sit Chuun, get placed, and start earning.