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Course

Machine Learning Operations (MLOps): Getting Started

IntermediateSkill Level
Updated 07/2026
Learn MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud.
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4 hr 30 min
12 videos
24 Exercises
1,250 XP
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Course Description

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.

Prerequisites

There are no prerequisites for this course
1

Welcome to the Machine Learning Operations (MLOps): Getting Started

This module provides the overview of the course
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2

Employing Machine Learning Operations

This module identifies ML practitioners' pain points before exploring the concept of DevOps in ML. You're introduced to the three phases of the ML lifecycle and automating the ML process.
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Machine Learning Operations (MLOps): Getting Started
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