Master AI Agents: LangGraph, RAG & MCP From Zero
Agentic AI is reshaping how software gets built, and this course gives you a structured path to actually master it rather than just experiment with prompts. Across 100 hands-on labs, you'll move from your first local AI assistant to building production-ready autonomous agents using LangGraph, retrieval-augmented generation, and MCP tool integrations. You'll learn how to design agents that reason, plan, remember context, and collaborate with each other, then take those skills further into real engineering territory: securing systems against prompt injection, monitoring agent behavior with OpenTelemetry and Grafana, and deploying everything on Kubernetes. This is built for developers who are tired of demo-level AI projects and want to understand how agentic systems actually run inside real organizations. Whether you're an aspiring AI engineer, an automation-focused builder, or an experienced developer expanding into AI infrastructure, each lab adds a practical, reusable skill. By the end, you'll have built a complete enterprise-grade agent platform from the ground up, using techniques you can apply directly to real projects.
🎬 TIMESTAMPS
SECTION 1: INTRODUCTION & FOUNDATIONS
0:00:00 Introduction
0:06:15 Foundations and First Success
0:09:59 Lab 1-10: Agentic AI Architecture, Python, Ollama & Local AI Assistant
SECTION 2: CORE AGENT ENGINEERING
0:45:09 Core Agent Engineering
0:55:47 Lab 11-20: Agent Lifecycle, Tools, Memory & Production Patterns
SECTION 3: LANGGRAPH FOUNDATIONS
1:31:37 LangGraph Foundations
1:42:00 Lab 21-30: Graph Nodes, Workflows, State & Enterprise Agents
SECTION 4: RETRIEVAL AND KNOWLEDGE SYSTEMS
2:18:22 RAG Systems
2:28:35 Lab 31-40: Embeddings, Vector Search, ChromaDB & Enterprise Knowledge
SECTION 5: MCP ENGINEERING
3:04:00 MCP Engineering
3:14:21 Lab 41-50: MCP Architecture, Servers, Clients & Enterprise Gateway
SECTION 6: MULTI-AGENT SYSTEMS
3:52:13 Multi-Agent Systems
4:02:57 Lab 51-60: Agent Communication, Swarms & Research Platform
SECTION 7: DATA ENGINEERING FOR AGENTS
4:38:41 Data Engineering
4:48:42 Lab 61-70: PostgreSQL, Redis, Kafka & Production Data Platform
SECTION 8: SECURITY AND COMPLIANCE
5:23:52 Security and Compliance
5:34:12 Lab 71-80: Threat Modeling, Prompt Injection, GDPR & EU AI Act
SECTION 9: OBSERVABILITY AND RELIABILITY
6:11:21 Observability and Reliability
6:21:01 Lab 81-90: OpenTelemetry, Tracing, Hallucination Detection & Reliability
SECTION 10: PRODUCTION DEPLOYMENT
6:55:57 Production Deployment
7:07:30 Lab 91-100: Docker, Kubernetes, GitOps, Terraform & Sovereign AI
SECTION 11: CONCLUSION
7:44:17 Conclusion
7:51:47 End of Course