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Grow with Google

Build and Deploy Machine Learning Solutions on Vertex AI

  • up to 7 hours
  • Intermediate

This course offers a comprehensive guide to building and deploying machine learning solutions on Vertex AI. Earn a digital badge from Google Cloud to showcase your skills and advance your cloud career.

  • Machine Learning Model Deployment
  • Cloud Computing
  • Data Management
  • Model Evaluation
  • Online Predictions

Overview

In this course, you will learn how to write and train models locally using Vertex Notebooks, host training code in containers, and manage image datasets for experiment tracking. You will also train a BigQuery ML classifier, activate training jobs using Vertex AI console, and create custom model evaluation components with KFP SDK. By the end of the course, you will be able to deploy trained models for online predictions and gain a digital badge to demonstrate your expertise.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    Spanish
    course language
  • Professional Certification
    upon course completion
  • Self-paced
    course format
  • Pre-recorded classes
    delivered online

Who is this course for?

Machine Learning Engineers

Professionals looking to enhance their skills in deploying machine learning models using Google Cloud's Vertex AI.

Data Scientists

Data scientists aiming to gain practical experience in building and deploying machine learning solutions on the cloud.

Cloud Professionals

Individuals interested in showcasing their cloud skills with a digital badge from Google Cloud.

Gain a competitive edge in the cloud industry by mastering Vertex AI for machine learning solutions. This course is ideal for intermediate learners looking to enhance their skills and earn a Google Cloud digital badge.

Pre-Requisites

1 / 3

  • Basic understanding of machine learning concepts

  • Familiarity with Google Cloud Platform

  • Experience with Python programming

What will you learn?

Introduction to Vertex AI
Learn the basics of Vertex AI and its role in machine learning model deployment.
Training Models Locally
Write and train models locally using Vertex Notebooks.
Hosting Training Code
Host your training code in containers and send it to Google Cloud Artifact Registry.
Image Dataset Management
Create managed artifacts of image datasets for experiment tracking.
Training with BigQuery ML
Train a BigQuery ML XGBoost classifier.
Activating Training Jobs
Activate a training job using the Vertex AI console.
Custom Model Evaluation
Create a custom model evaluation component with the KFP SDK.
Incorporating KFP Components
Incorporate pre-compiled KFP components into your pipeline.
Deploying Trained Models
Deploy your trained models to a Vertex endpoint for online predictions.
Querying Models
Query your model for online predictions and explanations.

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