https://github.com/ksm26/ai-agentic-design-patterns-with-autogen
Learn to build and customize multi-agent systems using the AutoGen. The course teaches you to implement complex AI applications through agent collaboration and advanced design patterns.
https://github.com/ksm26/ai-agentic-design-patterns-with-autogen
agent-collaboration agent-reflection agentic-design-patterns agentic-planning ai-agents ai-conversation ai-framework ai-workflow autogen blog-post-creation chess-game coding-agents complex-task-automation conversational-agents customer-onboarding financial-analysis microsoft-research multi-agent-systems tool-use
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Learn to build and customize multi-agent systems using the AutoGen. The course teaches you to implement complex AI applications through agent collaboration and advanced design patterns.
- Host: GitHub
- URL: https://github.com/ksm26/ai-agentic-design-patterns-with-autogen
- Owner: ksm26
- Created: 2024-05-30T21:14:26.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-17T11:29:00.000Z (12 months ago)
- Last Synced: 2025-03-28T16:18:54.042Z (3 months ago)
- Topics: agent-collaboration, agent-reflection, agentic-design-patterns, agentic-planning, ai-agents, ai-conversation, ai-framework, ai-workflow, autogen, blog-post-creation, chess-game, coding-agents, complex-task-automation, conversational-agents, customer-onboarding, financial-analysis, microsoft-research, multi-agent-systems, tool-use
- Language: Jupyter Notebook
- Homepage: https://www.deeplearning.ai/short-courses/ai-agentic-design-patterns-with-autogen/
- Size: 1.63 MB
- Stars: 69
- Watchers: 2
- Forks: 20
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🤖 [AI Agentic Design Patterns with AutoGen](https://www.deeplearning.ai/short-courses/ai-agentic-design-patterns-with-autogen/)
💡 Welcome to the "AI Agentic Design Patterns with AutoGen" course! The course will equip you with the knowledge and skills to build and customize multi-agent systems using AutoGen.
## Course Summary
In this course, you'll explore key principles of designing multi-agent systems and enabling agents to collaborate on complex tasks using the AutoGen framework. Here's what you can expect to learn and experience:
1. 🎭 **Conversational Agents**: Create a two-agent chat showing a conversation between two standup comedians using “ConversableAgent,” a built-in agent class of AutoGen.
2. 🎉 **Customer Onboarding**: Develop a sequence of chats between agents to provide a fun customer onboarding experience for a product using the multi-agent collaboration design pattern.
3. 📝 **Blog Post Creation**: Use the agent reflection framework to create a high-quality blog post with nested chats, where reviewer agents reflect on the blog post written by another agent.
4. ♟️ **Chess Game**: Implement a conversational chess game where two agent players can call a tool and make legal moves on the chessboard using the tool use design pattern.
5. 💻 **Coding Agent**: Develop a coding agent capable of generating the necessary code to plot stock gains for financial analysis and integrating user-defined functions into the code.
6. 📊 **Financial Analysis**: Create systems where agents collaborate and seek human feedback to complete a financial analysis task, generating code from scratch or using user-provided code.
By the end of the course, you’ll have hands-on experience with AutoGen’s core components and a solid understanding of agentic design patterns, ready to implement multi-agent systems in your workflows.
## Key Points
- 🛠️ Use the AutoGen framework to build multi-agent systems with diverse roles and capabilities for implementing complex AI applications.
- 📚 Implement agentic design patterns such as Reflection, Tool Use, Planning, and Multi-agent Collaboration using AutoGen.
- 🌟 Learn directly from the creators of AutoGen, Chi Wang and Qingyun Wu.
## About the Instructors
🌟 **Chi Wang** is a Principal Researcher at Microsoft Research, bringing extensive expertise in AI and multi-agent systems to guide you through this course.
🌟 **Qingyun Wu** is an Assistant Professor at Penn State University, specializing in AI and multi-agent collaboration, to help you master agentic design patterns.
🔗 To enroll in the course or for further information, visit [deeplearning.ai](https://www.deeplearning.ai/short-courses/).