RAG pipelines, AI agents and LLM engineering, taught through the same workflow a production AI team uses — prototype, ground it in real data, then ship it.
Real modules, real topics, real projects — pick a level to see exactly what you'll learn and build.
Python, APIs and the core concepts behind every LLM application.
Ground LLM answers in real data and build a working application around it.
Tool-using agents, orchestration and shipping something production-shaped.
Your capstone project takes you from a raw set of documents to a working assistant: chunking and embedding content, wiring up a vector database, and grounding an LLM's answers in your own data — then wrapping it into an agent that can take action.
Chunk, embed and retrieve real documents, then ground an LLM's answers in your own data.
Talk to an advisor for current fees, batch dates and mode of delivery.
