π‘ 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.
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:
- π Conversational Agents: Create a two-agent chat showing a conversation between two standup comedians using "ConversableAgent," a built-in agent class of AutoGen.
- π 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.
- π 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.
- βοΈ 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.
- π» 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.
- π 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, youβll have hands-on experience with AutoGenβs core components and a solid understanding of agentic design patterns, ready to implement multi-agent systems in your workflows.
- π οΈ Use the AutoGen framework to build multi-agent systems with diverse roles and capabilities for implementing complex AI applications.
- π Implement agentic design patterns such as Reflection, Tool Use, Planning, and Multi-agent Collaboration using AutoGen.
- π Learn directly from the creators of AutoGen, Chi Wang and Qingyun Wu.
π Chi Wang is a Principal Researcher at Microsoft Research, bringing extensive expertise in AI and multi-agent systems to guide you through this course.
π Qingyun Wu is an Assistant Professor at Penn State University, specializing in AI and multi-agent collaboration, to help you master agentic design patterns.
π To enroll in the course or for further information, visit deeplearning.ai.