Course
Production Machine Learning Systems
IntermediateSkill Level
Updated 07/2026
Google CloudCloud16 hr47 videos82 Exercises4,350 XPStatement of Accomplishment
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Prerequisites
There are no prerequisites for this course1
Introduction to Advanced Machine Learning on Google Cloud
This module previews the topics covered in the course and how to use Qwiklabs to complete each of your labs using Google Cloud.
2
Architecting Production ML Systems
This module explores what else a production ML system needs to do and how to meet those needs. You review how to make important, high-level, design decisions around training and model serving need to make in order to get the right performance profile for your model.
3
Designing Adaptable ML Systems
In this module, you learn how to recognize the ways that our model is dependent on our data, make cost-conscious engineering decisions, know when to roll back our models to earlier versions, debug the causes of observed model behavior and implement a pipeline that is immune to one type of dependency.
4
Designing High-Performance ML Systems
In this module, you identify performance considerations for machine learning models.Machine learning models are not all identical. For some models, you focus on improving I/O performance, and on others, you focus on squeezing out more computational speed.
5
Building Hybrid ML Systems
Understand the tools and systems available and when to leverage hybrid machine learning models.
6
Summary
7
Course Resources
Production Machine Learning Systems
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