AI agents are becoming a vital tool for automating tasks and enhancing decision-making across industries. However, understanding how to create these agents from scratch in Python can be daunting without the right foundation. From knowing where AI agents can be applied to understanding their underlying architecture, learning these fundamentals is key to building effective and efficient agents that deliver real-world value.
In the second part of this series, Richmond Alake, Staff Developer Advocate for AI and ML at MongoDB, teaches you how to put the concepts you learned yesterday into practice. You'll build an AI agent from scratch and test its capabilities.
This is part two of a two part session. Find part one here.
Key Takeaways:
- Learn how to build an AI agent from scratch using Python.
- Learn how to test the performance of your AI agent on real-world tasks.
- Learn how to make your AI agent robust and reusable.
