Agentic AI

Build agentic AI systems that take action through iterative, multi-step workflows. In this course taught by Andrew Ng, you’ll gain a fundamental understanding and practical knowledge to develop production-ready agentic applications, from design patterns to deployment and evaluation. This course is only available on DeepLearning.AI

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Build agentic design patterns: reflection, tool use, planning, and multi-agent workflows
Integrate AI with external tools: databases, APIs, web search, and code execution
Evaluate and optimize AI systems: performance metrics, error analysis, and production deployment

Why Enroll?

Agentic AI represents a new way of building software that leverages LLMs to complete some or all of the steps in complex tasks. Instead of generating single responses to prompts, agentic workflows enable AI to plan multi-step processes, execute them iteratively, and improve outputs through reflection and tool use. This course teaches you to build these sophisticated AI systems from the ground up.

You’ll master four design patterns that power agentic AI systems:

Reflection: AI critiques its own work and iterates to improve quality—like code review, but automated.
Tool Use: Connect AI to databases, APIs, and external services so it can actually perform actions, not just generate text.
Planning: Break complex tasks into executable steps that AI can follow and adapt when things don’t go as expected.
Multi-Agent: Coordinate multiple specialized AI systems to handle different parts of a complex workflow.

The course emphasizes practical implementation using Python, building each pattern from first principles before exploring frameworks, giving you the flexibility to customize AI workflows for your specific needs. You’ll learn to deconstruct business processes into agentic workflows, identifying where human-like iteration and tool interaction can automate complex tasks. Critical evaluation skills are woven throughout—you’ll build robust testing frameworks, conduct systematic error analysis, and optimize systems for production deployment.

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You’ll earn a certificate upon completing the course, recognizing your skills in building agentic workflows.

Instructor

Andrew Ng

A pioneer in the AI industry, Andrew Ng co-founded Google Brain and Coursera, led AI at Baidu, and has reached millions of learners with his machine learning courses.

5 Modules
Self-paced
Intermediate

Who this course is for

Software developers who want to apply AI techniques to build autonomous systems that handle multi-step workflows.

Professionals with intermediate-level Python programming skills to be able to follow along with the implementations.

Professionals with a basic understanding of large language models and APIs who want to deepen their practical skills.

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Course Syllabus

Module 1: Introduction to Agentic AI

Understand what makes AI “agentic” and why iterative, multi-step workflows outperform traditional single-prompt approaches. Learn to identify tasks suitable for agentic implementation and develop a framework for evaluation-driven development.

Module 2: Reflection Design Pattern

Master the foundational pattern where AI systems critique and improve their own outputs. Build workflows for database querying, chart generation, and document writing that get better through self-reflection.

Module 3: Tool Use Design Pattern

Enable your AI systems to interact with the world through tools. Learn multiple approaches including function calling, code execution, and the Model Context Protocol (MCP) for seamless tool integration.

Module 4: Practical Tips for Building Agentic AI

Develop essential skills for real-world deployment: creating robust evaluations, conducting error analysis, optimizing performance, and building reliable systems that work at scale.

Module 5: Planning and Multi-Agent Systems

Build the most sophisticated agentic patterns. Create AI that can formulate complex plans and coordinate multiple specialized agents to tackle large, complex problems.

Capstone Project: Research Agent

Apply everything you’ve learned to build a complete research agent that can gather information, analyze findings, and produce comprehensive reports—all through an autonomous agentic workflow.

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Learner reviews from other DeepLearning.AI courses

What I loved about the “AI for Everyone” course was the comprehensive coverage of essential AI topics, guided by the expertise of Andrew Ng. The course provided a clear roadmap for initiating and managing AI projects, from project selection to implementation. It also offered insights into building AI teams and introduced the technical tools necessary for AI success

Selami A.
Software QA Manager

Simple enough to make it easy to understand in spite of being a complex topic, inspiring speaker. Time well spent, and a good fit with “lifelong learning” approach.

Chris C.
DeepLearning.AI Learner

What stood out to me about this course was the clarity and simplicity with which complex AI concepts were explained. The real-life examples and case studies helped me grasp the practical implications of AI in different sectors. The interactive nature of the course made learning engaging and enjoyable.

Adeel B.
DeepLearning.AI Learner

I am an educator and looking to incorporate AI into my career and help my colleagues to do the same. The course did a great job explaining AI concepts to people like myself who are just learning about any of this for the first time.

Krystal L.
DeepLearning.AI Learner

I took this course purely out of curiosity. After becoming aware of ChatGPT and Midjourney and then taking a short course on engineering the prompts to get the desired result, I became more intrigued with the topic of AI. I found this most helpful with regards to getting an idea about what AI actually is as opposed to what Hollywood conditioned me to believe it might be.

John S.
DeepLearning.AI Learner

Loved the content. It brought simplicity to the complex topic of AI, separated signal from noise, presented a great flow and covered the most relevant topics.

Andrew’s knowledge and passion about the subject of AI was amazing. It was inspiring to listen to him, even via recorded videos. Its really great to be in this era of technology, as it makes it possible to get access to the wealth of knowledge so easily.

Muhammad S.
DeepLearning.AI Learner

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