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Artificial Intelligence
Artificial Intelligence
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DeepLearning.AI 2

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. By the end of the course, you will have hands-on experience with AutoGen’s core components and a solid understanding of agentic design patterns, ready to effectively implement multi-agent systems in your workflows.

  • 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 how to build and customize multi-agent systems for complex tasks.

Tech Professionals

Professionals seeking practical skills and knowledge to leverage the AutoGen framework effectively.

Why should you take this course?

Artificial Intelligence

Gain practical skills in building and customizing multi-agent systems using the AutoGen framework. Learn from the creators of AutoGen and be ready to implement agentic design patterns in your workflows. Ideal for Python developers, AI enthusiasts, and tech professionals.

Pre-Requisites

1 / 2

  • Basic Python coding experience

  • Interest in automating complex workflows using AI agents

What will you learn?

Introduction to AutoGen
Learn the basics of the AutoGen framework and its applications in building multi-agent systems.
ConversableAgent
Create a two-agent chat that shows a conversation between two standup comedians using the ConversableAgent class.
Multi-agent Collaboration
Develop a sequence of chats between agents to provide a fun customer onboarding experience for a product.
Agent Reflection Framework
Use the agent reflection framework to create a high-quality blog post with nested chat structures.
Tool Use Design Pattern
Implement a conversational 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 the necessary code to plot stock gains for financial analysis.
Collaborative Coding Agents
Develop systems where agents collaborate and seek human feedback to complete a financial analysis task.

Meet your instructors

  • Chi Wang

    Principal Researcher, Microsoft Research

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

  • Qingyun Wu

    Instructor, DeepLearning.AI

    Qingyun Wu is an Assistant Professor at Penn State University. He has a PhD in Computer Science from the University of California, Berkeley.

Upcoming cohorts

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Free