Generative AI & LLM Engineer Path
Developers who want to build production applications on large language models, from prompting to deployment.
4 stepsHands-on labsCapstone + portfolioA named role
Save $147 vs. courses separately
By the end, you can
What this path makes you able to do.
- Build with large language models: prompting, context, and the API model
- Ship retrieval-augmented generation, embeddings, tool use, and agents
- Take LLM systems to production with evaluation, guardrails, and observability
A guided journey, not a pile of courses
The 4-step path.
- 1View course
LLM Engineering Foundations
Prompting, tokens, and the API
- 2View course
Building LLM Applications
RAG, embeddings, tools, and agents
- 3View course
Productionizing LLM Systems
Eval, guardrails, and deployment
Capstone: build and ship an LLM application
A working retrieval-augmented application with evaluation, guardrails, and a deployment and observability plan
Every path is backed by
Hands-on labs. A final exam & capstone. A real role.
You finish with a portfolio you can show, a cumulative exam, and the skills to land the Generative AI / LLM Engineer role.
Not sure this is the one? Take the free fit and aptitude check first: twelve short questions, instant answer.