What if your AI couldthink, decide, and act—not just respond?

Welcome toAgentic AI Engineering, a hands-on specialization designed to help you buildautonomous, production-ready AI systems. Unlike traditional AI courses that focus only on prompts or APIs, this program teaches you how to buildend-to-end Agentic AI systemsthat can retrieve knowledge, use tools, and make decisions in real-world scenarios.

You’llstart with the foundations of Agentic AI and develop scalable applications using theMERN stack, integrating models like OpenAI and Gemini.As you progress, you will createAI agents that are powered by RAG and MCP, enabling dynamic responses, tool calling, and intelligent workflows.

You’llthen explore MCP architecture and tool ecosystems to build APIs and backend services that enable AI interaction with external systems. Finally,you’lllearn how to make use of AI memory with systems like vector databases (ChromaDBandpgVector) to create scalable, high-performance systems.

ThisAgentic AI Engineeringcourseis designed for Developers, backend engineers, and AI enthusiasts who want to move beyond chatbots and buildreal-world AI agents.

By the end,you’llbe able todesign, build, and deploy intelligent AI systemsused in modern applications.

Build the future of AInot just prompts, but systems.

Projet d'apprentissage appliqué

As part of thisAgentic AI Engineeringspecialization, you will work on real-life AI and development projects such as: 

• Building and configuring a full-stack development environment using MERN (MongoDB, Express, React, Node.js) 

• Creating scalable applications by integrating RAG (Retrieval-Augmented Generation) pipelines and advanced AI models like OpenAI and Gemini 

• Developing autonomous AI systems with Model Context Protocol (MCP) for real-time decision-making and tool interaction 

• Setting up andoptimizingvector databases likeChromaDBandpgVectorto enhance AI memory and real-time data processing 

• Designing and implementing an AI chat interface with React and integrating backend AI systems for dynamic responses 

• Integrating advanced AI functionalities like embeddings and context-based search to build intelligent and adaptive agents