Introduction

Do you know, that you can automate machine learning (ML) deployments and workflow? Yes, you heard it right. This can be done using Machine Learning Operations (MLOps), which are a set of rules and practices that simplify and automate ML deployments and workflows. Nowadays people are building AI and ML solutions that are solving real-world problems at a breakneck pace. These are possible only when you are including MLOps in your whole project. In this article, we’re bringing you the 6 most important and free courses on MLOps, offered by Google.

Also Read: A Comprehensive MLOps Learning Path: 2024 Edition

6 Free Google Courses on MLOps

As an aspiring data scientist or data enthusiast you need to have a clear understanding of the core concepts of MLOps. So, if you are stuck somewhere or don’t know where to master these concepts, this article is for you. This curated list will guide you into the world of MLOps with ease, as we have categorized the courses from basic to advanced level. So, let’s begin!

1. Machine Learning Operations (MLOps): Getting Started

This is the introductory course for beginners, which introduces you to the fundamentals of MLOps tools and the best practices for deploying, evaluating, monitoring, and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best-performing models.

After completing this fundamental course, you will earn the badge attached below. Moreover, you can boost your cloud career by showcasing the badge on Linkedin and showing the world the skills you have developed.

2. MLOps: Continuous Delivery and Automation Pipelines in Machine Learning

In this course, you will comprehend and discuss the techniques for implementing and automating continuous integration (CI), continuous delivery (CD), and continuous training (CT) for machine learning (ML) systems. Data science and ML are becoming core capabilities for solving complex real-world problems, transforming industries, and delivering value in all domains.

3. Build and Deploy Machine Learning Solutions on Vertex AI

This skill badge course is for professional Data Scientists and Machine Learning Engineers. The datasets and labs are built around high business impact enterprise machine learning use cases; these include retail customer lifetime value prediction, mobile game churn prediction, visual car part defection identification, and fine-tuning BERT for review sentiment classification.

4. ML Pipelines on Google Cloud

In this course, you’ll learn from Google Cloud’s cutting-edge ML pipeline developers and trainers. TensorFlow Extended (TFX), Google’s production machine learning framework for ML pipelines and metadata, will be covered in the first few topics. TFX pipeline components and orchestration will be covered.

5. Machine Learning Operations (MLOps) with Vertex AI: Manage Features

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring, and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Learners will get hands-on practice using Vertex AI Feature Store’s streaming ingestion at the SDK layer.

6. Production Machine Learning Systems

This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.

Conclusion

So there you have it, seven superb MLOps courses from Google – all available for free! Whether you’re just dipping your toes into machine learning operations or you’re aiming to polish your skills, these courses cover everything from the basics to more complex aspects of MLOps. Not only do you get to learn about deploying and optimizing ML systems, but you also get to earn some shiny badges to showcase on your LinkedIn profile. It’s a fantastic opportunity to boost your expertise and credibility in this rapidly growing field. Why not start one of these courses today and step up your game in the world of machine learning operations? Happy learning!