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

Build production-grade Autonomous Agents with MCP, RAG, Gemini, OpenAI and Signals using Angular & Node.js.

Preview this Course

GET COUPON CODE

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.

Description

Stop building basic chatbots. It is time to build Enterprise-Grade AI Agents.

Welcome to the Agentic AI Engineering program for Angular Developers.

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.

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.

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.

Key Technical Deep Dives:

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.

Angular Signals & AI Streaming: Learn to handle high-velocity token streams and Markdown rendering without freezing the UI, using Angular's latest reactivity primitives.

Advanced RAG Pipelines: Move beyond basics. We implement Vector Search using ChromaDB and pgVector, handling embeddings and context augmentation manually.

Native Tool Calling: Learn how to force LLMs to output strictly structured JSON to trigger functions in your code—the backbone of Agentic Automation.

The Tech Stack:

Frontend: Angular (Latest), Signals, TailwindCSS

Backend: Node.js, Express, TypeScript (Strict Mode)

AI Models: Google Gemini, OpenAI (GPT Models)

Vector Databases: ChromaDB, pgVector

Protocols: MCP (Model Context Protocol)

If you are ready to stop building "toy apps" and start building scalable, intelligent systems, enroll now.

Who this course is for:

• Full-Stack Developers who want to transition from traditional web apps to building AI-powered Agentic systems.
• Solutions Architects & Tech Leads who need to implement the new Model Context Protocol (MCP) standard in enterprise.
• AI Enthusiasts looking to master the Model Context Protocol (MCP) and modern Tool Calling standards.
• Software Engineers who need to implement RAG and Vector Search without relying on "black box" frameworks like LangChain.
• Freelancers & Consultants who want to offer high-value "Custom AI Agent" services to clients.

Share :