Learning Vertex AI: MLOps with Google Cloud

Learning Vertex AI: MLOps with Google Cloud

1h 39mIntermediate2023-05-05

Authors

Vaidheeswaran Archana

Vaidheeswaran Archana

Data Scientist, AI Engineer, and Data Product Manager

Soham Chatterjee

Soham Chatterjee

Machine Learning Lead

Course details

It seems like everyone is talking about AI these days. But did you know you can train and manage machine learning models using the new MLOps cloud solution from Google? In this course, learn how to manage your entire machine learning model’s lifecycle—from loading data to monitoring deployments—using Vertex AI to build models and maintain your applications.

Find out why Vertex AI has become so popular so quickly, not just within the tech industry, but all across the globe. Instructors Archana Vaidheeswaran and Soham Chatterjee show you the skills you need to know to get up and running with this powerful new tool. Along the way, take your Python and ML skills to the next level with data loading, feature engineering, training models and hyperparameter tuning, model deployment, and model monitoring.

Skills covered

Vertex AIMachine LearningGoogleArtificial Intelligence (AI)Learning

Concepts

Introduction

  • Learning Vertex AI
  • What you should know

Introduction to MLOps

  • MLOps lifecycle - ML development
  • MLOps lifecycle - Training
  • MLOps lifecycle - Deployment
  • Vertex AI walkthrough

Feature Engineering

  • Vertex AI feature store
  • Vertex AI data labeling

Training and Hyperparameter

  • Vertex AI AutoML
  • Vertex AI experiments
  • Vertex AI model registry
  • Vertex AI training

Model Serving and Deployment

  • Vertex AI prediction
  • Vertex AI TensorBoard
  • Vertex AI endpoints

Model Monitoring and Management

  • Vertex AI model monitoring
  • Vertex AI pipelines

Deploy Your Project Using Vertex AI

  • Challenge - Deploy a project
  • Solution - Deploy a project

Conclusion

  • Vertex AI vs. other MLOps platforms
  • What next
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