Start from first principles. Grow into production AI systems.
New to AI? Start with AI Engineering Fundamentals. Then move into RAG & Knowledge Systems Engineering, which begins with simple retrieval mental models and grows into measurable, secure and operational knowledge systems.
Plain-English entry points. Engineering depth underneath.
Foundation first, then focused specializations. Each stage reuses production disciplines rather than restarting from tool hype.
Start here. Learn how AI applications work, connect to models, use your own data, call tools safely, evaluate results and operate AI systems reliably.
Models · prompts · RAG · tools · evaluation · security · observability · productionOpen course →Beginner-entry, engineer-exit specialization for building evidence-grounded AI over trusted organizational knowledge.
Ingestion · chunking · embeddings · hybrid retrieval · reranking · grounding · provenance · evaluation · security · freshnessOpen course →Build controlled AI workflows that can use tools and complete multi-step tasks where model-driven decisions genuinely add value.
Workflows · tools · state · approvals · budgets · failure handlingLearn how organizations serve, monitor and operate AI models and applications at scale.
Serving · routing · evaluation pipelines · telemetry · governance · reusable platform capabilities