Building-Autonomous-Agentic-AI-Systems-for-Beginners-HandsOn
A Packt-published, hands-on course that teaches how to design, build and deploy agentic AI systems using frameworks such as Smolagents, CrewAI, MCP and n8n.
This course teaches the fundamentals of agentic AI, how it differs from traditional AI systems, and how reasoning, planning and tool use enable autonomous workflows, then covers the building blocks of agentic systems: LLMs, memory, embeddings, vector databases and RAG pipelines.
Hands-on sections build a standalone AI agent, an MCP server and client agent, multi-agent systems with CrewAI, an AWS monitoring multi-agent system, a cross-cloud system spanning AWS and Google Cloud, and agentic RAG systems including a course-intelligence agent. It also covers reflection, self-improvement, safety and guardrail techniques.
The course assumes familiarity with Python, a basic understanding of how LLMs work, and prior experience with AI.