The 4 Best MLOps Courses and Online Training for 2023

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4 Best MLOps Courses and Online Training

The process of transferring a model developed in an experimental environment to a

production web system is known as MLOps (machine learning operations). MLOps is used by data science professionals, DevOps, and machine learning engineers to coordinate the transition of the algorithm into production when an application is ready for launch. MLOps focuses on increasing automation and improving the quality of production machine learning while remaining compliant.

Keeping that in mind, we've put together a list of the bestMLOps certificationcourses and online training to look into if you want to improve your data science and machine learning skills for work or play. Although this is not an exhaustive list, it does include the best MLOps courses and online training from reputable providers. We made a point of mentioning and linking to relevant courses on each platform that may be of interest to you as well.

The Best MLOps Certification Courses

TITLE: Fundamentals of MLOps (Machine Learning Operations)

OUR OPINION: Google Cloud offers this 100% online training on intermediate-level subject matter with flexible deadlines. It takes approximately 16 hours to complete.

Courserais the platform used.

Participants in this course will learn about MLOps tools and best practises for deploying, evaluating, monitoring, and operating production ML systems on Google Cloud. MLOps is a discipline that focuses on the production deployment, testing, monitoring, and automation of machine learning systems. Professionals in Machine Learning Engineering use tools to continuously improve and evaluate deployed models. They work with (or can be) Data Scientists to create models that allow for speed and rigour in deploying the best performing models.

TITLE: Foundations of Applied Machine Learning

OUR TAKE: Machine learning expert Derek Jedamski demonstrates the Python programming language, machine learning techniques, and data cleaning examples to students.

LinkedInLearning is the platform.

In this course, the first in a two-part series on Applied Machine Learning, instructor Derek Jedamski delves into the fundamentals of machine learning, from exploratory data analysis


to evaluating a model to ensure it generalises to previously unseen examples. Rather than focusing on a specific machine learning algorithm, Derek focuses on providing you with the tools to solve nearly any type of machine learning problem.

TITLE: Uncovering the Mysteries of Machine Learning Operations (MLOps)

OUR OPINION: This Pluralsight intermediate-level training is only two hours long and will teach you the most important concerns and issues to consider when developing machine learning models for deployment.

Pluralsightis the platform.

Demystifying Machine Learning Operations (MLOps) is a course that will teach you how to incorporate machine learning operations into your machine learning project. First, you'll investigate how to implement machine learning operations (MLOps) practises in your

infrastructure. Following that, you'll learn about machine learning operations (MLOps) during model development. Finally, after model deployment, you'll learn how to use machine

learning operations (MLOps).

TITLE: Microsoft Azure Nanodegree Machine Learning Engineer

OUR OPINION: The nanodegree program at Udacity takes about three months to complete (at 5-10 hours per week). For the best chance of success with this module, students should have prior experience with Python, machine learning, and statistics.

Udacityis the platform.

Students will improve their skills in this program by building and deploying sophisticated machine learning solutions using popular open source tools and frameworks, as well as gaining practical experience running complex machine learning tasks using the built-in Azure labs accessible within the Udacity classroom.




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