“This course contains the use of artificial intelligence”

Master Agentic AI: From Foundations to Production-Ready Systems

This intensive 3-day course is designed to take you from understanding the basics of Agentic AI to building production-ready multi-agent systems that can operate in real-world business environments. You will go beyond simple prompting and learn how to design intelligent systems that can reason, act, use tools, and collaborate to complete complex tasks.

On Day 1, you will build a strong foundation in how AI agents actually work. You will learn the difference between chatbots, workflows, and agents, and understand core concepts like the ReAct loop (Think → Act → Observe). You will then dive into the anatomy of an AI agent, including system prompts, memory, tools, and output structures. By the end of the day, you will build your first working agent with tool integration and retrieval-based memory.

Day 2 focuses on scaling from single agents to multi-agent systems. You will explore powerful design patterns such as Planner–Executor, Researcher–Writer, and Critic–Improver, and understand why single agents fail in real-world scenarios. You will learn how to use modern orchestration frameworks like LangGraph, CrewAI, and AutoGen to design structured workflows. Through hands-on implementation, you will build a multi-agent system that collaborates across roles to solve end-to-end tasks.

On Day 3, you will transition from prototypes to production-ready AI systems. You will learn how to implement evaluation pipelines, including LLM-as-a-Judge, test cases, and regression testing. You will design guardrails and safety systems to prevent prompt injection, unsafe outputs, and tool misuse. You will also explore observability and monitoring, tracking inputs, outputs, latency, and failures. Finally, you will learn how to scale agent systems using cost optimization, parallelization, and caching, and design enterprise-grade architectures with API layers, orchestration layers, and governance.

Throughout the course, you will also dive into advanced topics like Agent + RAG (Retrieval-Augmented Generation) for knowledge grounding, Agent + automation (Zapier, n8n) for workflow execution, Agent + enterprise APIs for real-world integration, and Agent + UI (Streamlit) for building interactive applications.

The course culminates in a capstone project, where you will build a production-ready multi-agent system with tools, memory, evaluation, and guardrails—complete with a working demo and business use case.

By the end, you will not just understand Agentic AI—you will be able to design, build, and deploy scalable, reliable, and enterprise-ready AI systems that deliver real impact.