AI engineering
Ship production-ready AI products.
Go beyond demos with a practical engineering path covering retrieval, tool calling, evaluation, observability, and product decisions.
Quick answer
What is this page about?
This is for engineers who need to move from a promising demo to a dependable product. The focus is architecture, evaluation, deployment, and the decisions that make AI systems useful in production.
What you will learn
From understanding to application.
Design an AI product architecture around models, data, and users
Build retrieval pipelines with evaluation instead of guesswork
Connect tools and structured outputs to safe product workflows
Add observability, guardrails, and quality signals before launch
Ship and explain a production-minded AI project
The curriculum
A focused, useful sequence.
Move from model and data foundations into RAG, tool calling, evaluation, observability, and deployment patterns you can reuse in real products.
AI product architecture and model selection
Live instruction, guided practice, and feedback.
RAG pipelines, embeddings, and retrieval quality
Live instruction, guided practice, and feedback.
Tool calling, structured outputs, and workflow safety
Live instruction, guided practice, and feedback.
Evaluation, observability, and failure analysis
Live instruction, guided practice, and feedback.
Deployment, cost, security, and responsible operations
Live instruction, guided practice, and feedback.
Capstone: ship a production-ready AI application
Live instruction, guided practice, and feedback.
Frequently asked
Start with clarity.
Ship production-ready AI products. is designed with a clear starting point, guided practice, and mentor support. Beginners can start with the foundations before moving into applied projects.
Pricing
Choose your way in.
Every plan includes live mentor guidance, practical projects, recordings, community access, and a certificate of completion.
Corporate and private cohorts are available with custom pricing. Talk to us about teams.
Find your path
Which AI course is right for you?
Answer four quick questions and get a practical recommendation, learning roadmap, and next step.
Where are you starting?
1 / 4Make your next move