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Machine Learning on Google Cloud

This course teaches you how to build Vertex AI AutoML models without writing a single line of code; build BigQuery ML models knowing basic SQL; create Vertex AI custom training jobs you deploy using...

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$3,250 USD GSA  $2,697.73
Course Code GCP-ML
Duration 5 days
Available Formats Classroom
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This course teaches you how to build Vertex AI AutoML models without writing a single line of code; build BigQuery ML models knowing basic SQL; create Vertex AI custom training jobs you deploy using containers (with little knowledge of Docker0; use Feature Store for data management and governance; use feature engineering for model improvement; determine the appropriate data preprocessing options for your use case; write distributed ML models that scale in TensorFlow; and leverage best practices to implement machine learning on Google Cloud. Learn all this and more!

Skills Gained

This series of courses teaches participants the following skills:

  • Build, train, and deploy a machine learning model without writing a single line of code using Vertex AI AutoML.
  • Understand when to use AutoML and Big Query ML.
  • Create Vertex AI managed datasets.
  • Add features to a Feature Store.
  • Describe Analytics Hub, Dataplex, and Data Catalog.
  • Describe hyperparameter tuning using Vertex Vizier and how it can be used to improve model performance.
  • Create a Vertex AI Workbench User-Managed Notebook, build
  • a custom training job, and then deploy it using a Docker container.
  • Describe batch and online predictions and model monitoring.
  • Describe how to improve data quality.
  • Perform exploratory data analysis.
  • Build and train supervised learning models.
  • Optimize and evaluate models using loss functions and performance metrics.
  • Create repeatable and scalable train, eval, and test datasets.
  • Implement ML models using TensorFlow/Keras.
  • Describe how to represent and transform features.
  • Understand the benefits of using feature engineering.
  • Explain Vertex AI Pipelines.

Who Can Benefit

This class is intended for the following participants:

  • Aspiring machine learning data analysts, data scientists and data engineers
  • Learners who want exposure to ML using Vertex AI AutoML, BQML, Feature Store, Workbench, Dataflow, Vizier for hyperparameter tuning, and TensorFlow/Keras

Prerequisites

To get the most out of this specialization, participants should have:

  • Some familiarity with basic machine learning concepts
  • Basic proficiency with a scripting language, preferably Python

Course Details

Course Outline

  • How Google Does Machine Learning
  • Launching into Machine Learning
  • TensorFlow on Google Cloud
  • Feature Engineering
  • Machine Learning in the Enterprise
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