Vertex AI Agent Builder
Vertex AI Agent Builder lets developers, even those with limited machine learning skills, tap into the power of Google's foundation models, search expertise, and conversational AI technologies to create enterprise-grade generative AI applications. In this course, you learn how to use Vertex AI Agent Builder to create search engines and chat applications. You will then explore how to integrate these search engineers and chat applications into your own applications. Finally, you learn how to manage the tools built in Vertex AI Agent Builder in production.
What you will learn
- Explore Vertex AI as a platform for enterprise-ready generative AI.
- Create a search engine using Vertex AI Search.
- Create a chat application by using Vertex AI Agents.
- Integrate Vertex AI Agent Builder into your applications.
- Productionize search engines and chat applications created in Vertex AI Agent Builder.
Prerequisites
- Google Cloud Fundamentals: Core Infrastructure or equivalent Google Cloud experience.
Target audience
- Customers, Developers
Training Program
4 modules to master the fundamentals
Objectives
- Explore Vertex AI as a platform for enterprise-ready generative AI.
- Describe example use cases of Vertex AI Agent Builder.
Topics covered
- →Vertex AI
- →Vertex AI Agent Builder
- →Example use cases
Objectives
- Understand the main concepts of apps, engines, and data stores.
- Create a search engine using Vertex AI Search.
- Configure and integrate custom search engines.
Topics covered
- →Apps, engines and data stores
- →Data preparation
- →Creating a custom search engine
- →Configuration options
Activities
Lab: Integrate Search in Applications Using Vertex AI Search
Lab: Grounding LLMs Using Vertex AI Search
Objectives
- Understand the basic concepts of data store agents and Dialogflow CX.
- Create a chat application by using Vertex AI Agents.
Topics covered
- →Dialogflow CX basic concepts
- →Creating a chat app
- →Options deploying conversational agents
Activities
Lab: Create a Generative Chat App with Vertex AI Agents
Objectives
- Manage changing data and schemas in data stores.
- Explain security features of Vertex AI Agent Builder.
- Use monitoring and logging for Vertex AI Agent Builder apps.
- Troubleshoot Vertex AI Agent Builder applications.
Topics covered
- →Refreshing data and schemas
- →Security and DLP
- →Monitoring and logging
- →Troubleshooting
Activities
Lab: Maintaining Search Engines Using Vertex AI Search
Quality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
- Guided Labs — Guided practical exercises on software, hardware, or technical environments.
- Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Upcoming sessions
No date suits you?
We regularly organize new sessions. Contact us to find out about upcoming dates or to schedule a session at a date of your choice.
Register for a custom dateTrain multiple employees
- Volume discounts (multiple seats)
- Private or custom session
- On-site or remote