Build Production AI Agents with RAG & MCP

Overview

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Ready to revolutionize AI development? The world of AI is rapidly evolving, and building intelligent, autonomous agents is the next frontier. But how do you go from just understanding AI concepts to creating powerful, production-ready systems? In this course, you’ll not only learn the theory but also gain real-world experience by building AI agents using Gemini and OpenAI. You’ll start by setting up a robust Node.js backend and then integrating Gemini for effortless text generation. Dive deep into creating static RAG systems for advanced Q&A bots and use OpenAI to take your AI’s responses to the next level. Unlike other courses, this Agentic AI course gives you the tools to create scalable, real-world applications like customer service bots and knowledge bases, ensuring your skills are directly applicable in the industry. Whether you're a developer, data scientist, or AI enthusiast, this course will sharpen your AI development skills and prepare you for real-world AI challenges. Don’t just learn about AI—build the future of AI agents. Enroll now and take the first step toward mastering AI development!

Syllabus

Building the AI Chat Backend and Static RAG System

Develop a robust Node.js backend, integrate the Gemini API with a React chat interface, and implement a Static RAG system to deliver structured, knowledge-driven responses.

Embeddings and OpenAI-Based Answer Generation

Leverage embeddings and semantic search techniques to build a dynamic RAG Q&A system, integrating OpenAI for intelligent, context-aware answer generation.

MCP Server Foundation and Tool API Preparation

Establish a TypeScript backend, design real-world APIs, and apply MCP principles—Tools, Resources, and Prompts—to build scalable, intelligent AI agents.