Machine Learning in the Enterprise

This course is part of multiple programs. Learn more

Instructor: Google Cloud Training

What you'll learn

  •   Describe data management, governance, and preprocessing options
  •   Identify when to use Vertex AutoML, BigQuery ML, and custom training
  •   Implement Vertex Vizier Hyperparameter Tuning
  •   Explain how to create batch and online predictions, setup model monitoring, and create pipelines using Vertex AI

    • Skills you'll gain

  •   Feature Engineering
  •   Data Pipelines
  •   Google Cloud Platform
  •   Applied Machine Learning
  •   Data Governance
  •   MLOps (Machine Learning Operations)
  •   Predictive Modeling
  •   Machine Learning
  •   Data Management
  •   Workflow Management
  •   Continuous Monitoring

    • There are 10 modules in this course

    The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.

    Understanding the ML Enterprise Workflow

    Data in the Enterprise

    Science of Machine Learning and Custom Training

    Vertex Vizier Hyperparameter Tuning

    Prediction and Model Monitoring Using Vertex AI

    Vertex AI Pipelines

    Best Practices for ML Development

    Course Summary

    Series Summary

    Explore more from Machine Learning

    Machine Learning Essentials for Business and Technical Decision Makers

    Machine Learning Using SAS Viya

    Managing Machine Learning Projects

    Applying Machine Learning to your Data with Google Cloud

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