Agentic AI Architectures with Patterns, Frameworks and MCP

Agentic AI is the next frontier of artificial intelligence, shifting from simple prompt-response interactions to systems that actively plan, reason, and execute complex workflows. This course provides a deep dive into the architectural principles required to build robust, enterprise-grade multi-agent systems. You will move beyond basic API wrapper tutorials and master the essential design patterns that govern agent behavior, including the ReAct framework, reflection, planning, and swarm intelligence. By exploring the Model Context Protocol (MCP) and agentic RAG, you gain the technical proficiency to connect Large Language Models with real-world databases and internal tools securely. The curriculum emphasizes the full Agent Development Lifecycle (ADLC), teaching you how to structure orchestration versus choreography and how to implement human-in-the-loop controls effectively. Whether you are aiming to build autonomous e-shop agents or sophisticated research assistants, this course demystifies the chaotic landscape of agent frameworks by focusing on core systemic patterns. By the end of this journey, you will have the knowledge to design scalable, reliable agentic ecosystems that transition your AI projects from experimental prototypes to production-ready enterprise solutions that truly perform autonomous work.