Modern Agentic AI: MCP, RAG, AI Agents, LangGraph & Workflow

About this course

This course contains the use of artificial intelligence.I only charge a fee solely for the time invested in building this comprehensive curriculum.Stop Vibe Coding. Start Engineering.The AI industry is entering a new era.For years, most AI education focused on prompt engineering, chatbots, and simple API calls. Thousands of students learned how to create demos. Very few learned how to build systems.That gap is becoming increasingly expensive.Organizations are no longer hiring people who can simply connect to a language model. They are hiring engineers who can build retrieval systems, orchestrate agents, secure workflows, deploy infrastructure, implement governance, and operate AI reliably in production.The difference between a hobby project and a professional AI platform is massive.This course was designed to bridge that gap.Instead of teaching isolated tools, we guide you through a structured 100-Lab Engineering Journey that transforms beginners into practitioners capable of designing, deploying, and governing modern Agentic AI systems.A Complete Engineering ProgressionThis is not a collection of disconnected tutorials.Every lab builds on the previous one.You begin by understanding the modern Agentic AI ecosystem and building your local development environment. From there, you develop the engineering foundations required for production systems.You will master:Python for AI engineeringLocal LLM deploymentPrompt engineeringStructured outputsTool callingRetrieval-Augmented Generation (RAG)Vector databasesHybrid retrievalKnowledge systemsModel Context Protocol (MCP)AI agentsMulti-agent collaborationLangGraph workflowsSecurity engineeringObservability