AI

MCP Fundamentals

Learn how to build real applications with the Model Context Protocol (MCP), from first principles to advanced integrations. In this course, you will start by understanding the core MCP architecture and building your first server with Python and FastMCP. You will then add Tools, Resources, and Prompts, inspect them with MCP Inspector, and move on to building custom MCP clients that can work programmatically with LLMs through the Anthropic API.

From there, you will explore advanced features such as Elicitation for human-in-the-loop workflows, Roots for filesystem security, and Sampling for client-side AI execution. Finally, you will bring everything together by building a full-stack ChatGPT App that serves a React frontend from a Python MCP backend using the OpenAI Apps SDK.

By the end of the course, you will understand how MCP hosts, clients, and servers fit together, how to design reliable tool schemas and resources, and how to ship MCP-powered experiences that work in desktop clients, custom programs, and ChatGPT.

Context Engineering for AI

Explore context engineering as the foundation for building reliable, efficient AI systems. Learn how LLMs, prompting, RAG, agents, LangChain, and LangGraph work together in real applications. Understand the AI platform ecosystem and build practical workflows to choose the right tools for real-world use cases.

AI-Assisted Development for iOS

AI is coming for your job. And your life. Or maybe it isn’t. Who, other than Sarah Connor, knows? Whilst we wait for the AI apocalypse, join us on this course to discover how you can benefit from a selection of different LLM-based technologies to assist you with iOS development. Whether it’s creating a software spec, generating code, writing tests or debugging gnarly issues, we’ll explore how you can become more productive, and the limitations inherent in current AI state-of-the-art.