Agentic AI Master Class: Build Autonomous AI Systems with LLMs

This Agentic AI Master Class transitions developers from static LLM prompting to building fully autonomous, goal-oriented AI systems. The course covers foundational agentic design patterns — including Reflection, Tool Calling, Planning, and Multi-Agent Orchestration — alongside advanced topics such as RAG and memory architectures, the Model Context Protocol (MCP), and production deployment using FastAPI, Docker, and n8n. Students gain hands-on experience with leading frameworks including LangGraph, CrewAI, AutoGen, and LlamaIndex Agentic RAG. Module 1 begins with the core Agent Loop — Perception, Reasoning, Planning, Action, and Observation — and teaches reasoning techniques such as Chain-of-Thought (CoT), Tree-of-Thought (ToT), and the ReAct framework. Learners also build a single-agent researcher that self-corrects search queries using feedback loops. Later modules address multi-agent networks, Vector DB integration with persistent episodic and semantic memory, custom tool execution environments, and securing agents against prompt injection attacks. #AgenticAI #LLMDevelopment #AIEngineering #MultiAgentSystems #LangGraph #Lykstage #LykstageVideo #LykstageCreator #LykstageCommunity