This is the repository for the LinkedIn Learning course Building Agents with Vertex AI. The full course is available from LinkedIn Learning.
AI agents can serve as natural language interfaces to complex data systems by assisting users in finding data, contextualizing data, and performing tasks. In this course, you’ll learn how to use the Vertex AI Agent Builder—a powerful low-code environment—to build networks of AI agents that work together to access data and solve complex tasks through a chat interface. Through practical examples, you’ll explore how to build agents that query documents, connect to APIs, and use custom Python tools to query, retrieve, and synthesize data from an external website.
See the readme file in the main branch for updated instructions and information.
To follow along with this course and build your own agents, you need an activated Google Cloud account. You can set one up at https://cloud.google.com. During the setup process you will be asked provide your name, address, email address, and a valid credit card.
This repository has an /assets folder with materials you can use as you follow along with the course. The assets are provided as-is and you can use them and edit them in any way you like to build your own agents.
The files provided are:
/assets/google-maps-geocoding-api-OpenAPI-schema.yaml/assets/vancouver-neighbourhoods.txt
You'll be prompted when to access and use these files in the course.
The Vertex AI Agent Builder is a rapidly evolving project and while this course gives you a comprehensive breakdown of how to use this tool, there are many features and details not covered in the course.
To bridge this gap there is a documentation.md file in the root of this repo with links to relevant documentation and further details.
Morten Rand-Hendriksen
Senior Staff Instructor, Speaker, Web Designer, and Software Developer
Check out my other courses on LinkedIn Learning.