Agentic AI Foundations: Build RAG & MCP Chatbots
About this course
The next wave of AI isn’t about better prompts—it’s about building systems that think, retrieve, and act on their own. Most AI applications today stop at generating responses. But real-world systems need more they must access the right data, make decisions, and execute tasks seamlessly. This course is your gateway into Agentic AI, where RAG and MCP come together to create truly intelligent applications. You’ll build a full-stack AI system from the ground up designing retrieval pipelines, implementing embeddings and ranking, and enabling tool-driven workflows. Develop a modern Angular chat interface, power it with a Node.js backend, and integrate leading models like OpenAI and Gemini to create dynamic, context-aware experiences. This Agentic AI course is not about theory or isolated demos you’ll engineer a complete, production-ready AI chatbot that mirrors real industry use cases. Built for developers ready to move beyond experimentation and create meaningful AI solutions. Do not just deploy AI create systems that think, adapt, and deliver. Enroll now and start your journey into the future of AI engineering.
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What you'll learn
- Build retrieval-augmented generation (RAG) pipelines for context-aware AI applications
- Implement embeddings and ranking systems for information retrieval
- Integrate OpenAI and Gemini models into full-stack applications
- Develop a chat interface using Angular and Node.js
- Create tool-driven workflows using the Model Context Protocol (MCP)
- Design agentic AI systems that can retrieve data and execute tasks
Course objectives
- Engineer a complete, production-ready AI chatbot system
- Understand the architecture of agentic AI applications
- Implement retrieval and ranking mechanisms for AI systems
- Build both frontend and backend components of an AI application
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