Coursera MOOC / Non-credit 0

Machine Learning Operations (MLOps) on Google Cloud

Name: Machine Learning Operations (MLOps) on Google Cloud
Price: 49 USD
Availability: InStock

About this course

This learning path is designed for data scientists and ML engineers looking to bridge the gap between machine learning prototypes and production-ready systems on Google Cloud. Learners will explore the full MLOps lifecycle, including feature management with Vertex AI Feature Store, robust model evaluation for predictive and generative AI, and the orchestration of automated workflows. The path concludes with advanced training on building production-grade pipelines using the Kubeflow SDK, Google Cloud components, and AI-driven development with the Data Science Agent.

67/100

CourseAsk score

What the provider tells you: 31/45
Who stands behind it: 20/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

Understand the MLOps lifecycle
Manage features with Vertex AI Feature Store
Evaluate machine learning models for both predictive and generative AI
Orchestrate automated workflows
Build production-grade ML pipelines using Kubeflow SDK and Google Cloud components

Course objectives

Bridge the gap between machine learning prototypes and production systems
Implement robust model evaluation strategies
Facilitate automated workflows for machine learning operations

Machine Learning Cloud Computing #google cloud #machine learning #mlops #model evaluation #vertex ai #automated workflows #production systems #ai-driven development #kubeflow #feature management

$49.00

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