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Machine Learning Operations (MLOps): Getting Started

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google...

By Google Cloud Training on Coursera

About This Course

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models. This course is primarily intended for the following participants: Data Scientists looking to quickly go from machine learning prototype to production to deliver business impact. Software Engineers looking to develop Machine Learning Engineering skills. ML Engineers who want to adopt Google Cloud for their ML production projects. >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

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Frequently Asked Questions

How much does Machine Learning Operations (MLOps): Getting Started cost?

Visit the Machine Learning Operations (MLOps): Getting Started course page for current pricing and available discounts.

Who teaches Machine Learning Operations (MLOps): Getting Started?

Machine Learning Operations (MLOps): Getting Started is taught by Google Cloud Training, Google Cloud.

What skill level is Machine Learning Operations (MLOps): Getting Started for?

This course is designed for beginner learners.

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Students0
Duration8 hours
LevelBeginner
Languageen
PlatformCoursera