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Introduction to Google Vertex AI
Introduction
Difficulty
Beginner
Duration
38m
Students
333
Ratings
4.7/5
Description

In this course, we will introduce Google Vertex AI.

Learning Objectives

  • How to create a managed dataset in Vertex AI
  • How to use that dataset to train your own machine learning model
  • How to use your models to make predictions

Intended Audience

  • Data Engineers
  • Machine Learning Engineers

Prerequisites

  • A basic understanding of machine learning concepts
  • Access to a GCP account
Transcript

Hello, and welcome to “Introduction to Google Vertex AI”.  My name is Daniel Mease and I’ll be taking you through this course.  I am a trainer at Cloud Academy with over 20 years of software and web development experience.

This course is intended for:

  • Data Engineers

  • Machine Learning Engineers

By completing this course, you will learn the following:

  1. How to create a managed dataset in Vertex AI

  2. How to use that dataset to train your own machine learning model

  3. How to use your models to make predictions

The following prerequisites are recommended:

  • A basic understanding of machine learning concepts

  • Access to a GCP account

Feedback on our courses is valuable.  When this video was recorded, all course information was accurate.  But Google is constantly updating its products and services.  So, if you notice any issues, please contact us at support@cloudacademy.com.  Also feel free to share any criticisms or suggestions for improvement.

About the Author
Students
37260
Courses
44
Learning Paths
16

Daniel began his career as a Software Engineer, focusing mostly on web and mobile development. After twenty years of dealing with insufficient training and fragmented documentation, he decided to use his extensive experience to help the next generation of engineers.

Daniel has spent his most recent years designing and running technical classes for both Amazon and Microsoft. Today at Cloud Academy, he is working on building out an extensive Google Cloud training library.

When he isn’t working or tinkering in his home lab, Daniel enjoys BBQing, target shooting, and watching classic movies.

Covered Topics