Agentic AI: Production Grade AI Agents using CrewAI and AWS

Agentic AI is rapidly evolving from simple chatbot implementations into complex, autonomous workflows. This course provides a comprehensive roadmap for moving beyond basic LLM prompting into the realm of professional-grade autonomous agent design. Students are guided through the architectural intricacies of building multi-agent systems using CrewAI, a powerful framework for orchestrating agent collaboration. By leveraging AWS Bedrock and AgentCore, the curriculum ensures that you are building on a robust, enterprise-ready infrastructure. A key focus is placed on the practical integration of Retrieval-Augmented Generation (RAG) and the Model Context Protocol (MCP) to provide agents with real-time, domain-specific intelligence. Furthermore, the course addresses the critical lifecycle of an AI agent, covering advanced topics like persistent memory, inter-agent communication (A2A), and sophisticated observability using Langfuse. By teaching you how to apply the 'LLM-as-a-Judge' framework for data-driven performance evaluations and essential security measures, this course helps learners transition from writing experimental scripts to architecting resilient, production-grade applications that can solve complex, multi-step business problems independently and reliably.