The 4 Best MLOps Courses and Online Training for 2022

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The editors of Solutions Review have compiled this list of the best MLOps courses and online training to consider.

SR finds 106MLOps (short for Machine Learning Operations) is the process of taking a model developed in an experimental environment and putting it into a production web system. When an application is ready to launch, MLOps is coordinated between data science professionals, DevOps, and machine learning engineers to get the algorithm into production. One of the key features of MLOps is to increase automation and improve the quality of production machine learning while controlling compliance requirements.

With that in mind, we’ve compiled this list of the best MLOps courses and online training to consider if you’re looking to develop your data science and machine learning skills for work or play. This is not an exhaustive list, but a list that showcases the best MLOps courses and online training from trusted online platforms. We made sure to mention and link to related courses on each platform that might also be worth exploring.

Best MLOps Courses

TITLE: Fundamentals of MLOps (Machine Learning Operations)

OUR OPINION : Offered by Google Cloud, this 100% online training offers flexible deadlines on intermediate level subjects. It takes about 16 hours to complete.

Platform: Coursera

The description: This course introduces participants to MLOps tools and best practices for deploying, assessing, monitoring, and operating production ML systems on Google Cloud. MLOps is a discipline focused on deploying, testing, monitoring, and automating ML systems in production. Machine learning engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or may be) Data Scientists, who develop models, to enable speed and rigor in the deployment of the most successful models.

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TITLE: Applied Machine Learning: Foundations

OUR OPINION : Data scientist Derek Jedamski specializes in machine learning and shows students the Python programming language, machine learning techniques, and examples of data cleaning.

Platform: LinkedIn Learning

The description: In this course, the first installment of the two-part Applied Machine Learning series, instructor Derek Jedamski explores the foundations of machine learning, from exploratory data analysis to model evaluation for ensure that it generalizes to new examples. Instead of focusing on a specific machine learning algorithm, Derek focuses on giving you the tools to effectively solve almost any type of machine learning problem.

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TITLE: Demystifying Machine Learning Operations (MLOps)

OUR OPINION : This mid-level Pluralsight course is just two hours long and will teach you the key concerns and issues to consider when developing machine learning models post-deployment.

Platform: Plural view

The description: In this course, Demystifying Machine Learning Operations (MLOps), you will learn how to implement machine learning operations in your machine learning project. First, you’ll learn how to apply machine learning operations (MLOps) practices for your infrastructure. Next, you will learn how machine learning operations (MLOps) when developing a model. Finally, you will learn how to apply machine learning operations (MLOps) after deploying the model.

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TITLE: Become a Machine Learning Engineer for Microsoft Azure Nanodegree

OUR OPINION : The Udacity nanodegree program takes approximately 3 months (5-10 hours per week). Students should bring prior experience with Python, machine learning, and statistics to have the best chance of success with this module.

Platform: audacity

The description: In this program, students will improve their skills building and deploying sophisticated machine learning solutions using popular open-source tools and frameworks, and gain hands-on experience performing machine learning tasks. complex using the built-in Azure labs accessible in the Udacity classroom.

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NOW READ: The Best Coursera Machine Learning Training to Consider

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Timothy King
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