Start from first principles. Grow into production AI systems.
New to AI? Start with AI Engineering Fundamentals. Then move into RAG & Knowledge Systems Engineering or the beginner-first Agentic AI Engineering path, which starts with agents versus workflows and builds through security, evaluation, recovery and a controlled production capstone. The LLMOps path now spans local model serving through production AI platform operations, with the complete 16-module course, scenario-heavy formal assessment and distinct completion/assessment-verified credential paths.
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 →Beginner-first path from agents versus workflows through safe tools, state and memory, then planning, approvals, MCP, security, evaluation and production operations.
16 modules · tools · state · planning · multi-agent · approval · reliability · MCP · security · observability · evaluation · recovery · production capstoneOpen course →Beginner-first visual path for serving, tracing and operating AI applications, growing from local model APIs into reliable reusable platform capabilities.
16 modules · visual request paths · voice Learning Coach · model serving · routing · performance · evaluation · RAG/agents · security · Kubernetes · AI platform · capstoneOpen course →