Agentic AI Full‑Stack Masterclass: RAG, MCP & AI Agents

<div>Stop building basic chatbots. It is time to build Enterprise-Grade AI Agents.</div><div><br></div><div>Welcome to the <b><u>Agentic AI Engineering program for Angular Developers</u></b>.</div><div><br></div><div>Most AI tutorials focus on Python or React. But the enterprise world runs on Angular. In this course, we bridge the gap. We will architect a Full-Stack Agentic System from scratch using Angular (Latest) and Node.js, integrating cutting-edge protocols like MCP (Model Context Protocol) and Deterministic RAG pipelines.</div><div><br></div><div>Why Angular for AI? Agentic AI requires handling massive streams of data—token streaming, tool outputs, and real-time state changes. Angular’s Signals and RxJS architecture make it the superior choice for building complex, stable AI Dashboards.</div><div><br></div><div>What you will build: We will engineer a professional AI platform. You won't just learn syntax; you will learn the Clean Architecture patterns required to deploy autonomous systems in a corporate environment.</div><div><br></div><div>Key Technical Deep Dives:</div><div><ul><li><span style="font-size: 1rem;">The Model Context Protocol (MCP): Master the new industry standard. You will build Custom MCP Servers in Node.js to connect your AI to internal databases and expose them as tools to Gemini or OpenAI.</span></li><li><span style="font-size: 1rem;">Angular Signals & AI Streaming: Learn to handle high-velocity token streams and Markdown rendering without freezing the UI, using Angular's latest reactivity primitives.</span></li><li><span style="font-size: 1rem;">Advanced RAG Pipelines: Move beyond basics. We implement Vector Search using ChromaDB and pgVector, handling embeddings and context augmentation manually.</span></li><li><span style="font-size: 1rem;">Native Tool Calling: Learn how to force LLMs to output strictly structured JSON to trigger functions in your code—the backbone of Agentic Automation.</span></li></ul></div><div><br></div><div>The Tech Stack:</div><div><ul><li><span style="font-size: 1rem;">Frontend: Angular (Latest), Signals, TailwindCSS</span></li><li><span style="font-size: 1rem;">Backend: Node.js, Express, TypeScript (Strict Mode)</span></li><li><span style="font-size: 1rem;">AI Models: Google Gemini, OpenAI (GPT Models)</span></li><li><span style="font-size: 1rem;">Vector Databases: ChromaDB, pgVector</span></li><li><span style="font-size: 1rem;">Protocols: MCP (Model Context Protocol)</span></li></ul></div><div><br></div><div>If you are ready to stop building "toy apps" and start building scalable, intelligent systems, enroll now.</div>

What you'll learn:

• Architect and build a complete Full-Stack Agentic AI application using Angular, Node.js, and Express.
• Implement advanced Retrieval Augmented Generation (RAG) pipelines with embeddings, vector search, and context augmentation.
• Master the Model Context Protocol (MCP) by building custom MCP Servers in Node.js to expose real-world tools to LLMs.
• Build a production-ready Chat Interface in Angular that handles streaming responses, Markdown rendering, and tool outputs.
• Set up and manage Vector Databases (ChromaDB and pgVector) to store high-dimensional embeddings for semantic search.
• Create Static RAG Systems using JSON and math-based Cosine Similarity to understand the core algorithms of retrieval.
• Implement Native Tool Calling with Gemini and OpenAI to turn natural language into executable code functions.
• Connect your RAG Engine as an MCP Tool, creating a modular system where Agents can "choose" to search your database.