MLOps (Machine Learning Operations) Fundamentals

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Course Features

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Duration

16 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

16 hours

Course Description

This course introduces participants the MLOps tools, best practices, and MLOps methods for deploying, evaluating and monitoring production ML systems on Google Cloud. MLOps refers to the testing, monitoring and automation of ML systems in manufacturing. Machine Learning Engineering professionals employ tools to continuously improve and evaluate the models they have deployed. They can work with Data Scientists (or could be), who create models to allow speed and rigor when deploying the most performant models.

This course is intended for Data Scientists who want to rapidly move from prototype to production and deliver business impact. Software Engineers who want to learn Machine Learning Engineering skills. ML Engineers looking to adopt Google Cloud in their ML production projects.

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Identify and use core technologies required to support effective MLOps.

Configure and provision Google Cloud architectures for reliable and effective MLOps environments.

Adopt the best CI/CD practices in the context of ML systems.

Implement reliable and repeatable training and inference workflows.

Course Instructors

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Google Cloud Training

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The Google Cloud Training team is responsible for developing, delivering and evaluating training that enables our enterprise customers and partners to use our products and solution offerings in an ef...

Course Accreditations

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