Stage 5: Exploration of AI Application Scenarios

Agentic AI course taught by Andrew Ng, teaching how to build AI systems that can autonomously perform complex tasks, mastering the four design patterns of reflection, tool use, planning, and multi-agent collaboration.

Start Learning AI →
AgenticAIAndrewNgAIAgentsWebSiteVideoFreeEnglish

Agentic AI Course Detailed Introduction

Course Overview

Agentic AI with Andrew Ng is a course launched by DeepLearning.AI, focusing on building AI agent systems, personally taught by Andrew Ng, a pioneer in the field of artificial intelligence. This course teaches how to build AI agent systems that can autonomously execute tasks through iterative, multi-step workflows.

Course Features:

  • 📚 5 Modules - A complete, systematic learning path
  • ⏰ Approx. 6 Hours - Self-paced learning
  • 🎯 Intermediate Difficulty - Suitable for learners with some foundational knowledge
  • 🆓 Free Course - Available exclusively on the DeepLearning.AI platform
  • 🎓 Certificate of Completion - Earn a skill certification upon course completion

What is Agentic AI?

Agentic AI represents a new way of building software, leveraging Large Language Models (LLMs) to complete some or all steps in complex tasks. Unlike traditional single prompt-response patterns, agentic workflows enable AI to:

  • 📋 Plan multi-step processes - Break down complex tasks into actionable steps
  • 🔄 Execute iteratively - Continuously refine output quality
  • 🛠️ Use tools - Connect to databases, APIs, and external services
  • 🤔 Self-reflect - Evaluate and improve its own output

Core Design Patterns

The course will delve into the four core design patterns that underpin Agentic AI systems:

1. Reflection

AI can critically examine its own work and iteratively improve quality – much like automated code review.

Application Scenarios:

  • Automated code review and optimization
  • Document quality improvement
  • Self-correction of output results

2. Tool Use

Connect AI to databases, APIs, and external services, enabling it to truly perform actions, not just generate text.

Application Scenarios:

  • Database queries and operations
  • Web search and information retrieval
  • Code execution and testing
  • Email sending and calendar management

3. Planning

Break down complex tasks into actionable steps that AI can follow and adjust when things don't go as expected.

Application Scenarios:

  • Task decomposition and scheduling
  • Automated project management
  • Adaptive workflow design

4. Multi-Agent Collaboration

Coordinate multiple specialized AI systems to handle different parts of a complex workflow.

Application Scenarios:

  • Team collaboration simulation
  • Specialized task division
  • Distributed processing for complex systems

Course Outline

Module 1: Introduction to Agentic Workflows

  • Welcome (2 minutes)
  • What is Agentic AI? (5 minutes) - Understanding the essence of Agentic AI
  • Degrees of Autonomy (5 minutes) - Analyzing levels of autonomy
  • Benefits of Agentic AI (4 minutes) - Advantages of Agentic AI
  • Agentic AI Applications (7 minutes) - Practical application scenarios
  • Task Decomposition (8 minutes) - Identifying steps in a workflow
  • Evaluation Agentic AI (Evals) (5 minutes) - An evaluation-driven development framework
  • Agentic Design Patterns (7 minutes) - Overview of design patterns
  • Module 1 Quiz (10 minutes) - Module quiz
  • Try the Research Agent (10 minutes) - Hands-on with a research agent

Module 2-5: Advanced Topics

Subsequent modules of the course will delve into the implementation details of each design pattern, culminating in the construction of a complete research agent capable of:

  • Gathering information
  • Analyzing findings
  • Generating comprehensive reports
  • Executing autonomous workflows

Hands-on Project: Research Agent

The core hands-on project of the course is to build a fully functional research agent that can:

# Example Workflow
1. Plan research strategy
2. Call a web search engine
3. Download relevant web pages
4. Synthesize and rank findings
5. Draft an outline
6. Edit for consistency
7. Generate a Markdown report

Project Features:

  • 🔍 Automated information gathering
  • 📊 Intelligent analysis and synthesis
  • 📝 Generation of structured reports
  • 🔄 Multi-step iterative optimization

Learning Methodology

Technical Implementation

  • Pure Python - Build from first principles, without hiding framework details
  • Framework Agnostic - Learn core concepts applicable to any agent framework
  • Step-by-step - Understand fundamentals first, then explore framework tools

Practical Skills

  • ✅ Deconstruct business processes into agentic workflows
  • ✅ Identify tasks suitable for agentic implementation
  • ✅ Build robust testing frameworks
  • ✅ Conduct systematic error analysis
  • ✅ Optimize systems for production deployment

Evaluation and Optimization

The course particularly emphasizes evaluation-driven development (Evals), which is key to building effective agents:

Core Capabilities:

  • 📈 Performance metric design
  • 🐛 Error analysis methodologies
  • 🔍 Workflow tracing (Traces)
  • 🎯 Component-level optimization
  • 🚀 Production deployment readiness

Andrew Ng's Insight:

"I've found that the biggest predictor of whether someone can effectively build agents is if they know how to drive a disciplined process of evaluation and error analysis. Teams that don't know how to do this can spend months tweaking agents and make almost no progress."

Who This Course Is For

Ideal Learners

  • 💻 Software Developers - Who want to apply AI techniques to build autonomous systems that handle multi-step workflows
  • 🐍 Python Programmers - With intermediate Python programming skills
  • 🤖 AI Practitioners - With a basic understanding of Large Language Models (LLMs) and APIs, looking to deepen their practical skills

Prerequisites

  • Foundational Python programming
  • Basic understanding of Large Language Models (LLMs)
  • Experience with API calls (helpful but not required)

Course Value

Why Take This Course?

  1. Master Cutting-Edge Skills - Agentic AI is one of the most in-demand skills in today's AI job market.
  2. Hands-on Experience - Build production-ready agent applications from scratch.
  3. Systematic Approach - Learn proven design patterns and best practices.
  4. Flexible Application - Apply core concepts using any framework once understood.
  5. Career Advancement - Significantly outperform most teams building agents.

Example Application Scenarios

  • 📝 Content generation and editing
  • 🔬 In-depth research and analysis
  • 💼 Customer service automation
  • 📈 Marketing workflow automation
  • 👨‍💻 Code generation and review
  • ⚖️ Legal document compliance checks
  • 🏥 Healthcare research
  • 📊 Business product research

Instructor Profile

Andrew Ng

  • 🎓 Pioneer in the field of Artificial Intelligence
  • 🧠 Co-founder of Google Brain
  • 📚 Co-founder of Coursera
  • 🏢 Former Chief Scientist at Baidu
  • 👨‍🏫 Creator of machine learning courses that have impacted millions of learners

Learning Tips

  1. Complete one lesson daily - Maintain learning consistency
  2. Hands-on practice - Follow the course to build projects
  3. Deep understanding - Grasp principles rather than memorizing frameworks
  4. Experiment and innovate - Try applying learned patterns to your own projects
  5. Join the community - Participate in DeepLearning.AI forum discussions

Course Outcomes

Upon completing this course, you will be able to:

✅ Understand the core concepts and benefits of Agentic AI ✅ Implement the four key agentic design patterns ✅ Build production-ready agent applications ✅ Evaluate and optimize agent systems ✅ Identify business scenarios suitable for agentic implementation ✅ Build agents using any framework or pure Python ✅ Earn a DeepLearning.AI certification

Summary

This is a highly practical course, personally taught by Andrew Ng, a top expert in the AI field. The course not only imparts theoretical knowledge but also emphasizes the development of practical skills, especially evaluation-driven development, a crucial skill often overlooked by many teams. Whether you want to build your own AI applications or gain a competitive edge in your career, this course is an unmissable learning opportunity for 2025.

Course Link: https://www.deeplearning.ai/courses/agentic-ai/