GCP200AIAGENTBUILDER

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.

✓ Formation officielle Google CloudNiveau Intermediate⏱️ 1 jour (7h)

Ce que vous allez apprendre

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.

Prérequis

Google Cloud Fundamentals: Core Infrastructure or equivalent Google Cloud experience.

Public cible

Customers, Developers

Programme de la Formation

4 modules pour maîtriser les fondamentaux

Objectifs

Explore Vertex AI as a platform for enterprise-ready generative AI.
Describe example use cases of Vertex AI Agent Builder.

Sujets abordés

→Vertex AI
→Vertex AI Agent Builder
→Example use cases

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

Teaching Methods Used

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).

Evaluation and Monitoring System

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.