AI Agents: From Foundations to Enterprise Systems

About this course

Disclaimer: This course contains the use of artificial intelligence(AI).

AI agents are rapidly transforming how software is built, decisions are made, and work gets done across industries. This course is a comprehensive, hands-on journey into designing, building, and deploying intelligent AI agents—from foundational concepts to enterprise-grade systems. Over 52 structured weeks, learners progress step by step through the full lifecycle of agentic AI without relying on a single capstone project, ensuring continuous, practical learning every week.

You begin by mastering the core foundations of AI agents, including agent architectures, perception–action loops, reasoning, planning, and memory. Early modules focus on understanding how large language models power modern agents, how prompts differ from programs, and how agents decompose complex goals into executable tasks. Through guided labs, you build your first agents, add memory, enable tool usage, and implement structured reasoning patterns that go far beyond simple chatbots.

As the course progresses, you move into agent frameworks, orchestration, and multi-agent collaboration. You learn how agents communicate, delegate tasks, resolve conflicts, and operate as coordinated systems rather than isolated components. Hands-on labs emphasize real execution—building sequential and parallel workflows, debugging agent failures, evaluating outputs, and optimizing for latency and cost. You gain practical experience designing agents that are reliable, explainable, and measurable.

A major focus of the course is knowledge-driven and data-aware agents. You build retrieval-augmented agents, integrate structured and unstructured data sources, work with documents, and design long-term memory systems that persist and evolve over time. You also explore advanced capabilities such as multi-modal agents that reason across text, images, and audio, as well as real-time and event-driven agents that respond dynamically to changing inputs.

The course then

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