Course
MLOps for Business
BasicSkill Level
Updated 01/2025TheoryMachine Learning3 hr14 videos45 Exercises3,150 XP3,775Statement of Accomplishment
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Discover MLOps for Business
Learn the essential concepts and practices of MLOps, an emerging set of tools and techniques for automating and scaling machine learning applications. Machine learning model development used to be a lengthy manual task, and most models never made it into production. With MLOps, businesses can effectively scale and automate the design, development, and operation of machine learning models.Learn to Use Machine Learning Operations in Your Business
This course will teach you what MLOps is and how you can use it to become a fully mature machine-learning company. You will learn about the requirements for MLOps, the tools, techniques, and people involved, and how to avoid common pitfalls. You’ll start by learning about the main elements of MLOps and why it is critical for businesses that want to design, develop, and operate multiple machine learning applications.Explore the MLOps Life Cycle
Next, you’ll explore the entire MLOps life cycle, from design to development, deployment, and operations. In Chapter 3, you’ll learn about the main challenges and risks of deploying machine learning models in practice. Finally, you’ll look at the best practices and case studies for successfully implementing MLOps in the real world.By the end of the course, you'll have a deep understanding of how to design, develop, and operate machine learning applications at scale and will be able to leverage the impact of machine learning on your business.Prerequisites
Machine Learning for Business1
Introducing MLOps
The first chapter will introduce MLOps and why it is necessary for businesses that want to design, develop, and operate multiple machine learning applications simultaneously. You will learn about the main elements of MLOps, such as scaling and automation, its benefits, and why MLOps remain challenging. You will also explore what it takes to start the MLOps journey both from a technological and managerial perspective.
2
The MLOps Life Cycle
In the second chapter, you’ll learn about the entire MLOps life cycle from design to development, deployment, and operations. You’ll explore why monitoring is essential for productive machine learning applications and why we must regularly re-train machine learning models.
3
MLOps: From Theory to Practice
In the third chapter, you will move from theory to practice and discover the main challenges and risks of deploying machine learning models. You’ll also learn how MLOps teams successfully operate and what management can do to foster successful scaling machine learning.
4
MLOps in the wild
The final chapter will demonstrate how to successfully jumpstart your business's MLOps journey by discussing best practices and pitfalls to avoid. Finally, you’ll examine the different levels of MLOps maturity and conclude the course with a real-life case study about designing, developing, and operating a machine learning application for critical production processes.
MLOps for Business
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FAQs
Is this a coding course or a conceptual course?
This is a theory-based course with no coding exercises. It focuses on the business concepts, strategies, and management practices needed to scale machine learning operations.
What will I understand about the MLOps life cycle after this course?
You will understand the full cycle from design through development, deployment, operations, monitoring, and model retraining, plus why each stage matters for production ML.
Who is this course designed for?
It targets business leaders, managers, and non-technical stakeholders who need to understand how to scale and automate machine learning applications within their organizations.
Does this course cover MLOps maturity levels?
Yes. The final chapter discusses different levels of MLOps maturity and how to assess where your organization stands on the path to fully automated ML operations.
What prerequisite knowledge is required?
You only need the Machine Learning for Business course. No programming experience is necessary since all content is presented at a conceptual and strategic level.
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