Master AI coding assistants like GitHub Copilot and Cursor to write faster, cleaner code. Learn advanced prompt strategies and IDE integrations to supercharge your daily development workflow.

Build your first production-grade LLM applications. Understand the core patterns of AI engineering, including chains, routers, and evaluators, to create reliable and scalable AI features.

Deep dive into advanced prompt engineering techniques. Learn to structure context effectively, manage token limits, and use few-shot prompting to get consistent, high-quality outputs from any model.

Automate complex business processes using AI. Design resilient workflows that can handle errors, retry failed steps, and integrate with external APIs to replace manual human labor.

Unlock the power of the Model Context Protocol to connect LLMs to your own data and tools. Build custom servers that allow AI to safely read files, access databases, and execute code.

Move beyond simple chatbots to autonomous agents. Learn the architecture of agentic systems, including memory, planning, and tool use, to build software that can act on its own.

Coordinate teams of specialized agents to solve complex problems. Explore frameworks for multi-agent collaboration, delegation, and consensus to tackle tasks too big for a single model.

Expand your applications beyond text. Integrate vision, image generation, and voice capabilities to create rich, immersive user experiences that interact with the world in new ways.

Apply everything you've learned to build a significant AI application. Work in a small team to architect, build, and deploy a production-ready solution that solves a real-world problem.

Showcase your work to the community. Present your capstone project, demonstrate its capabilities, and receive feedback from peers and instructors in our final demo day celebration.