Smart Analytics, Machine Learning, and AI on Google Cloud

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Course Overview

Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

Who Should Attend

Data Engineers

Course Objectives

    • Differentiate between ML, AI and deep learning.
    • Discuss the use of ML API’s on unstructured data.
    • Execute BigQuery commands from notebooks.
    • Create ML models by using SQL syntax in BigQuery.
    • Create ML models without coding using Vertex AI AutoML.

Course Outline

  • Course Introduction
  • Introduction to Analytics and AI
  • Prebuilt ML Model APIs for Unstructured Data
  • Big Data Analytics with Notebooks
  • Production ML Pipelines
  • Custom Model Building with SQL in BigQuery ML
  • Custom Model Building with Vertex AI AutoML
  • Course Summary

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Class Dates & Times

Class times are listed Central time

This is a 1-day class

Class dates not listed.
Please contact us for available dates and times.