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Machine Learning Operations

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May 1, 2024 Updated July 10, 2025 14 minute read
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Machine Learning Operations (MLOps) is a topic that learners and students of online courses may be interested in learning about. Learners and students may self-study. They may wish to learn Machine Learning Operations to satisfy their curiosity, to meet academic requirements, or to use Machine Learning Operations to develop their career and professional ambitions. 

Machine Learning Operations (MLOps) is a set of practices that help data scientists and engineers to manage the lifecycle of machine learning models, from development to deployment and monitoring. 

Why learn Machine Learning Operations?

There are many reasons to learn Machine Learning Operations. Some of the most common reasons include: 

Path to Machine Learning Operations

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We've curated eight courses to help you on your path to Machine Learning Operations. Use these to develop your skills, build background knowledge, and put what you learn to practice.
Sorted from most relevant to least relevant:

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Reading list

We've selected four books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Machine Learning Operations.
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Python: Real World Machine Learning
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Provides a comprehensive overview of MLOps, covering the entire lifecycle of machine learning models, from development to deployment and monitoring. It is written by an experienced practitioner who has implemented MLOps in production at scale.
Python: Real World Machine Learning
Kindle Edition
$$$
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Machine Learning Engineering
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Focuses on the engineering aspects of machine learning, providing guidance on how to build robust and scalable ML systems. It is written by an experienced practitioner who has built and deployed many ML systems in production.
Machine Learning Engineering
Paperback
$$
Machine Learning Engineering
Kindle Edition
$$
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Machine Learning Design Patterns
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Provides a collection of design patterns for machine learning systems. It is written by three experienced practitioners who have built and deployed many ML systems in production.
Machine Learning Design Patterns: Solutions to...
Paperback
$$
(Deutsch) Design Patterns für Machine Learning:...
Kindle Edition
$$
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Large Scale Machine Learning with Python
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Focuses on the engineering aspects of machine learning, providing guidance on how to build and deploy scalable, robust ML systems. It is written by an experienced practitioner who has built and deployed many ML systems in production.
Large Scale Machine Learning with Python
Paperback
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Large Scale Machine Learning with Python
Kindle Edition
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