Beginner's Guide to building Autonomous AI Agents with Open Source Frameworks
AI Agents, LLM, GenAI
Shivay Lamba
AI agents are becoming fundamental building blocks of modern applications, thanks to their capability of understanding context with the help of the LLMs, but with added capability to interact with systems, files. AI agents that can meaningfully interact across platforms while maintaining context aren't just for large tech companies anymore as we have a number of open source AI Agent frameworks now which developers can leverage. This beginner-friendly, hands-on tutorial shows the process of creating autonomous AI agents using opensource frameworks. From learning the core concepts of Agents, to understanding how to create, deploy, and manage AI agents that can handle real-world tasks.
We'll break down the complexities of AI agent development into understandable components. Starting with basic concepts and progressing to functional implementations, participants will learn how to create, deploy, and manage AI agents that can handle real-world tasks with the help of the Open Source AI Agent framework. Finally we will have a hands on demo.
canela Workshop
€50
Max. Attendees: 50
Free registration for Early Bokeron ticket holders and a discount
for all others
Key Takeaways
Understand the fundamental architecture of AI agents
Build a basic AI agent using open source framework like Eliza
Design agent-to-agent communication patterns
Deploy agents that can interact across platforms
Target Audience
Software Engineers (any level)
Software Architects
Data Scientists
Machine Learning Engineers
Engineering leaders exploring business use-cases to integrate AI capabilities into their products
Requirements
A laptop (Windows, Mac, or Linux)
Have Python installed in their system
Have at least one IDE/Code Editor
High level knowledge of basic Gen AI concepts like how LLMs / Vector search work is good to have (optional but encouraged).
