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DeepLearning.AI

AI Agentic Design Patterns with AutoGen

  • up to 1 hour
  • Beginner

In this course, you will learn how to build and customize multi-agent systems using the AutoGen framework. Gain hands-on experience with agentic design patterns and be ready to implement multi-agent systems in your workflows.

  • AutoGen framework
  • Multi-agent systems
  • Agentic design patterns
  • Reflection
  • Tool use

Overview

In AI Agentic Design Patterns with AutoGen, you will learn to build and customize multi-agent systems, enabling agents to take on different roles and collaborate to accomplish complex tasks using AutoGen. You will create various projects, including a two-agent chat, a customer onboarding experience, a high-quality blog post, a conversational chess game, and a coding agent for financial analysis. By the end of the course, you will have a solid understanding of agentic design patterns and be ready to implement multi-agent systems effectively.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Self-paced
    course format
  • Live classes
    delivered online

Who is this course for?

Python Developers

Individuals with basic Python coding experience looking to automate complex workflows using AI agents.

AI Enthusiasts

People interested in learning about multi-agent systems and their applications in AI.

Tech Professionals

Professionals seeking to enhance their skills in implementing agentic design patterns for complex AI applications.

This course offers practical skills and knowledge to leverage the AutoGen framework for building multi-agent systems. Ideal for Python developers, AI enthusiasts, and tech professionals, it covers key agentic design patterns and prepares you to implement complex AI applications.

Pre-Requisites

1 / 2

  • Basic Python coding experience

  • Interest in automating complex workflows using AI agents

What will you learn?

Introduction to AutoGen
Overview of the AutoGen framework and its capabilities in building multi-agent systems.
Agentic Design Patterns
Learn about key design patterns such as Reflection, Tool use, Planning, and Multi-agent collaboration.
Building a Two-Agent Chat
Create a conversation between two standup comedians using the ConversableAgent class.
Customer Onboarding Experience
Develop a sequence of chats between agents for a fun customer onboarding experience.
High-Quality Blog Post
Use the agent reflection framework to create a system where reviewer agents reflect on a blog post written by another agent.
Conversational Chess Game
Implement a chess game where two agent players can call a tool and make legal moves on the chessboard.
Coding Agent for Financial Analysis
Create a coding agent capable of generating code to plot stock gains and integrate user-defined functions.
Collaborative Coding Agents
Develop systems where agents collaborate and seek human feedback to complete a financial analysis task.

Meet your instructors

  • Chi Wang

    Instructor, DeepLearning.AI

    Chi is a Principal Researcher at Microsoft Research with over 10 years of experience in systems & theory for data platforms and data science. He is the creator of FLAML, an open source library for AutoML and tuning.

  • Qingyun Wu

    Assistant Professor, Penn State University

    Qingyun Wu is an Assistant Professor at Penn State University. He was a Postdoctoral Researcher at Microsoft.

Upcoming cohorts

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