Full Stack Agentic AI

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Provider

Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 10 hours a week
Sessions

Self-Paced
Level

Beginner

Found in

Overview

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Build real-world Agentic AI systems—not just chatbots. Most developers rely on tools like ChatGPT or Google Gemini, but quickly hit limits: no memory, weak reasoning, and little ability to interact with real data or APIs. Traditional AI apps can respond, but they can’t truly act, decide, or scale in production environments. This 3-course specialization changes that. You will begin by creating RAG full-stack AI apps using Angular and Node.js, then explore MCP server design, tool-calling systems, and agent workflows, and lastly go into production-grade architectures with vector databases, MongoDB, and distributed RAG pipelines. By the end, you become capable of building smart agents that retrieve knowledge, call APIs, manage structureddata as wellasmake autonomous decisions. You’ll master RAG, MCP, embeddings, and vector databases while also gaining practical experience with real-world tools like customer systems, order workflows, and external APIs. This also prepares you for AI engineering and system design interviews with confidence. What makes this Agentic AI certification course different is its focus on true full-stack agentic architecture, going beyond theory to help you build production-ready AI systems end to end. This is designed for developers, AI engineers, and students who want to move beyond basic AI API usage and build powerful, real-world intelligent systems. Start building AI that actually works in production. Enroll now.

Syllabus

Course 1: Agentic AI Foundations: Build RAG & MCP Chatbots
Course 2: MCP Servers & Agentic AI Architecture
Course 3: Advanced Agentic AI: Production Data Architecture

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AI isn’t the future anymore production-ready AI systems are. Are you ready to build them? Most developers learn how to call AI models. But the real advantage lies in building systems that retrieve the right data, process context intelligently, and scale reliably in production. That’s the gap this course closes. In this Agentic AI course, you’ll build a complete RAG pipeline using pgVector and PostgreSQL configuring vector databases, storing embeddings, & executing high-performance similarity search. You’ll design intelligent query pipelines with context construction and prompt engineering to generate precise, grounded outputs. You’ll then integrate RAG with MCP to create AI agents capable of handling real customer and order workflows. Finally, you’ll architect a production-ready MongoDB layer designing schemas, optimizing queries, & migrating services from mock data to scalable systems. What makes this different? You’re not learning isolated tools you’re building a real, end-to-end AI architecture used in modern production environments. Perfect for developers and AI engineers who want to move from experimentation to real impact. Enroll now and stay ahead of the curve.
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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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Imagine building an AI that doesn’t wait for prompts but actively runs your backend, selects the right tools, and completes tasks end-to-end. Most AI applications are limited to generating answers. But real-world systems require structured execution, intelligent workflows, and scalable architecture and that’s where most developers fall behind. In this course, you will build MCP-based AI systems that go beyond responses. You will implement backend logic using services and controllers, build MCP servers, and define tools, resources, and prompts to enable AI to execute in a controlled manner. Get hands-on experience with tool deployments using Gemini and OpenAI, request-response cycles, and agent controllers that cover autonomous workflows. You will also work with vector databases such as ChromaDB and pgVector to enhance context retrieval, accelerate data ingestion, and produce intelligent AI outputs. This Agentic AI course is designed for developers looking to level up and build agent-powered, production-ready systems for real-world industry needs. Stop building AI that just responds start building AI that operates. Enroll now and lead the next wave of intelligent systems.