Question 1

What is the refund policy?

Accepted Answer

If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

Question 2

Can I just enroll in a single course?

Accepted Answer

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Question 3

Is financial aid available?

Accepted Answer

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Question 4

Can I take the course for free?

Accepted Answer

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.

Question 5

Is this course really 100% online? Do I need to attend any classes in person?

Accepted Answer

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Question 6

What is machine learning engineering for production? Why is it relevant?

Accepted Answer

Machine learning engineering for production refers to the tools, techniques, and practical experiences that transform theoretical ML knowledge into a production-ready skillset.

Effectively deploying machine learning models requires competencies more commonly found in technical fields such as software engineering and DevOps. Machine learning engineering for production combines the foundational concepts of machine learning with the functional expertise of modern software development and engineering roles.

Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well. With machine learning engineering for production, you can turn your knowledge of machine learning into production-ready skills.

Question 7

What is the Machine Learning Engineering for Production (MLOps) Specialization about?

Accepted Answer

The Machine Learning Engineering for Production (MLOps) Specialization covers how to conceptualize, build, and maintain integrated systems that continuously operate in production. In striking contrast with standard machine learning modeling, production systems need to handle relentless evolving data. Moreover, the production system must run non-stop at the minimum cost while producing the maximum performance. In this Specialization, you will learn how to use well-established tools and methodologies for doing all of this effectively and efficiently.

In this Specialization, you will become familiar with the capabilities, challenges, and consequences of machine learning engineering in production. By the end, you will be ready to employ your new production-ready skills to participate in the development of leading-edge AI technology to solve real-world problems.

Question 8

What will I be able to do after completing the Machine Learning Engineering in Production (MLOps) Specialization?

Accepted Answer

By the end of the Machine Learning Engineering for Production (MLOps) Specialization, you will be ready to:

Question 9

What background knowledge is necessary for the Machine Learning Engineering for Production (MLOps) Specialization?

Accepted Answer

Who is the Machine Learning Engineering for Production (MLOps) Specialization for?

Machine Learning Engineering for Production (MLOps) Specialization

Course Features

Course Description

Module 1: Introduction to Machine Learning in Production

Module 2: Machine Learning Data Lifecycle in Production

Module 3: Machine Learning Modeling Pipelines in Production

Module 4: Deploying Machine Learning Models in Production

Course FAQs