Key Takeaways from the course
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Develop advanced AI agents using the AutoGen framework.
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Explore and customize tools use suit specific applications.
Course curriculum
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1
Introduction to AutoGen
- Course Introduction
- What is AutoGen and Why we use It?
- Agent Classes in Autogen
- Hands-On: Conversable Agents
- Quiz
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2
Conversation Patterns
- Intro to Different Conversation Patterns
- Sequential Chat
- Hands-On: Sequential Chat
- Quiz
- Agents with Tool Use
- Hands-On: Tool Use
- Agents with Code Execution + Hands on
- Quiz
Who Should Enroll
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For those on their journey to mastering AI Agents, ready to explore different frameworks and make a mark in the tech world.
Qingyun Wu, Penn State University and AG2
Qingyun Wu is an Assistant Professor at Penn State University and Co-creator of AG2 (formerly AutoGen). She has previously worked at Yahoo, Adobe, and Microsoft.
Chi Wang - Google DeepMind and AG2
Chi Wang is a Senior Staff Research Scientist at Google DeepMind and the Co-creators of AG2 (formerly AutoGen). He has 15+ years of experience and is also the creator of FLAML, a widely used open-source library for AutoML and tuning.
About the Instructors
Apoorv Vishnoi - Head of Training, Analytics Vidhya
Apoorv Vishnoi is the Head of Training at Analytics Vidhya. With over a decade of experience in AI, he has held diverse roles, including developing AI models to address industry challenges, advising companies on implementing AI processes, and teaching AI to CXOs, professionals, and Parliamentarians.
FAQ
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What is AutoGen?
AutoGen is a framework that simplifies the development of chatbots using an agent-based architecture, allowing for flexible and scalable conversational interactions.
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What are the key conversation patterns in AutoGen?
AutoGen offers 4 key conversation patterns-Two-Agent Chat ,Sequential Chat, Group Chat, Nested Chat
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How is Autogen different from CrewAI?
Autogen automates multi-agent AI task orchestration, while CrewAI focuses on seamless collaboration between humans and AI agents.
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Will I receive a certificate?
Yes, upon successful completion of the course and assignments, you’ll receive a certificate.
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Does this course cover advanced topics?
Yes, the course provides in-depth coverage of advanced conversational patterns and hands-on projects to equip you with practical skills.
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What are the prerequisites for this course?
Basic knowledge of Python and familiarity with AI concepts is recommended, but no prior experience with AutoGen is required.
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Are there hands-on activities in this course?
Yes, the course includes hands-on activities such as creating conversable agents, implementing sequential chats, and enhancing agents with tool use and code execution.