Building and Deploying AI Agents with LLMs and LangChain

About this course

This three-course specialization guides AI practitioners and developers through the complete journey of building practical AI agent systems — from single-agent architecture to multi-agent collaboration to production deployment. You will master modular agent design using LangGraph for graph-based workflows, Pydantic-AI for structured validation, and Mem0 for persistent memory, building agents that perceive, reason, and act across real-world scenarios. As you progress, you will design multi-agent collaboration systems using CrewAI and Agno — defining planner, executor, reviewer, and critic roles with shared memory and communication patterns. The final course brings everything together by integrating LLMs from OpenAI and Anthropic into orchestrated workflows, adding production-ready state management, deploying via FastAPI, and implementing monitoring and evaluation pipelines. By the end, you will be able to architect, coordinate, and deploy multi-agent systems integrated with external APIs for enterprise automation.

Course objectives

• master the principles of agent architecture
• create agents capable of perception, reasoning, and action
• define roles for agents in multi-agent systems
• build monitoring and evaluation pipelines for AI deployments