Courses
MLOps for Business
基本的技能水平
更新 2025年1月TheoryMachine Learning3小时14 videos45 Exercises3,150 XP3,692成就声明
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试试DataCamp for Business课程描述
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.先决条件
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.