The Modern Data Engineering Playbook

Data engineering has never been more consequential. The rise of LLMs, RAG systems, and AI-native applications hasn't made pipelines less important; it's made them the foundation on which everything else depends. Across four intensive, hands-on workshops, you'll rebuild your understanding of the data stack from the ground up. Lakehouse architecture, semantic layers, DataOps practices like CI/CD and observability, and the full pipeline behind real AI systems: RAG ingestion, embedding lifecycles, and vector store delivery.

You'll also learn what happens after you ship. How to instrument LLM pipelines, catch dataset drift and prompt regressions before they become incidents, and build feedback loops that make your systems smarter over time. Whether you're a data engineer stepping into AI or a seasoned practitioner modernising your stack, this course gives you the blueprints to build data infrastructure that's reliable, observable, and ready for the AI era.