🏆SFEIR is the Google Cloud EMEA Training Partner of the Year 2025🤝New partnership: Official GitLab Training🤖New training: AI-Augmented Developer
🏆SFEIR is the Google Cloud EMEA Training Partner of the Year 2025🤝New partnership: Official GitLab Training🤖New training: AI-Augmented Developer
GCP200VERTEXAI

Vertex AI for Machine Learning Practitioners

This instructor-led one-day course is designed for engineers and data scientists familiar with machine learning models who want to become proficient in using Vertex AI for custom model workflows. This practical, hands-on course will provide you with a deep dive into the core functionalities of Vertex AI, enabling you to effectively leverage its tools and capabilities for your ML projects.

Google Cloud
✓ Official training Google CloudLevel Intermediate⏱️ 1 day (7h)

What you will learn

  • Understand the key components of Vertex AI and how they work together to support your ML workflows.
  • Configure and launch Vertex AI Custom Training and Hyperparameter Tuning Jobs to optimize model performance.
  • Organize and version your models using Vertex AI Model Registry for easy access and tracking.
  • Configure serving clusters and deploy models for online predictions with Vertex AI Endpoints.
  • Operationalize and orchestrate end-to-end ML workflows with Vertex AI Pipelines for increased efficiency and scalability.
  • Configure and set up monitoring on deployed models

Prerequisites

  • Experience building and training custom ML models
  • Familiar with Docker

Target audience

  • Machine Learning Engineers, Data Scientists

Training Program

3 modules to master the fundamentals

Topics covered
  • →Understand Containerized Training Applications
  • →Understand Vertex AI Custom Training and Tuning Jobs
  • →Understand how to track and version your trained models in Vertex AI Model Registry
  • →Understand Online Deployment with Vertex AI Endpoints
Topics covered
  • →Understand Kubeflow
  • →Understand pre-built and lightweight Python components
  • →Understand how to compile and execute pipelines on Vertex AI
Topics covered
  • →Understand Feature Drift and Skew
  • →Understand Model Monitoring for models deployed to Vertex AI Endpoints

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Upcoming sessions

March 18, 2026
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May 7, 2026
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July 10, 2026
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September 11, 2026
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November 6, 2026
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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.

790€ excl. VAT

per learner

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