Knowledge that answers back.
Build a document Q&A system that retrieves relevant information and uses it to answer questions.
RAG · Embeddings · RetrievalThe outcome is what you can build.
Build real projects.Show what you can do.
Turn 13 weeks of hands-on learning into working AI projects. Show your thinking, explain your decisions and give people something they can actually try.
See how you’ll get thereProjects you’ll build.
Skills you can explain.
An agent with a game plan.
Create an assistant that breaks down tasks, connects tools and follows a workflow you designed.
Agents · MCP · LangGraphYour own AI application.
Bring the pieces together in a capstone with a usable interface, a GitHub repository and a live demo.
Streamlit · FastAPI · DeploymentBuild it. Explain it.
Make it your own.
Every project is a chance to practice the decisions behind the code: how to structure data, choose tools, handle errors and make an application useful.
Your final capstone brings those decisions together in a project you can walk through with an instructor, a teammate or a prospective employer.
Explore all 13 weeks ↗- A repository that shows your work
- A README that explains your approach
- A live demo people can explore
- An architecture you can talk through
After the capstone,
choose your direction.
Target-company briefs
Understand what your target companies are building and the technology their job descriptions call for.
Tailored MVP directions
Use what you learned to build a focused project aligned with a company’s needs.
A more focused introduction
Hiring-manager contacts and a project pitch help you share relevant work with the people you want to reach.
Project outcomes depend on your participation and completion. Interviews and offers remain employer decisions.