Ready to Level Up Your ML Workflow? Explore 5 MLOps Courses from Google

Emily Johnson
Emily Johnson
3 Min Read
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If you’re eager to build and deploy robust machine learning systems to production, diving into MLOps (Machine Learning Operations) is the way to go. And who better to learn from than Google? Here are five top-notch MLOps courses offered by Google that will help you master the fundamentals of production machine learning systems, focusing on Google’s Vertex AI platform.

Production Machine Learning Systems

Before delving into MLOps, it’s crucial to grasp how machine learning systems function in a production environment. This course provides a comprehensive overview of implementing machine learning systems in production, covering static, dynamic, and continuous training and batch and online processing. Key modules include architecting production ML systems, designing adaptable ML systems, designing high-performance ML systems, and building hybrid ML systems.

Machine Learning Operations (MLOps): Getting Started

This introductory course on MLOps is designed to familiarize you with deploying, testing, monitoring, and evaluating machine learning systems in production. You’ll learn about the tools and best practices for MLOps, with a focus on Google’s Vertex AI platform. Modules cover topics such as employing machine learning operations and an introduction to Vertex AI and MLOps on Vertex AI.

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

Building on your foundational knowledge of MLOps, this course delves deeper into MLOps on the Google Cloud platform, explicitly focusing on the Vertex AI feature store. You’ll learn how to deploy, monitor, and operate ML systems on Google Cloud, exploring the capabilities of the Vertex AI feature store.

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ML Pipelines on Google Cloud

This course offers an in-depth exploration of building and orchestrating ML pipelines on the Google Cloud Platform. You’ll learn how to build and orchestrate ML pipelines using TensorFlow Extend (TFX), Google’s production ML platform, as well as topics like CI/CD for machine learning, automating ML pipelines, and using Cloud Composer to orchestrate continuous training pipelines.

Build and Deploy Machine Learning Solutions on Vertex AI

In this hands-on course, you’ll tackle real-world ML use cases to train and deploy machine learning solutions using Google’s Vertex AI platform. From retail customer lifetime value prediction to fine-tuning BERT for sentiment classification, you’ll work on various enterprise ML use cases while learning to leverage AutoML effectively.

In conclusion, mastering MLOps is essential for building and deploying machine learning solutions at scale. By enrolling in these courses from Google, you’ll gain the skills and knowledge needed to excel in this rapidly evolving field. Whether you’re a seasoned ML practitioner or just starting, these courses offer valuable insights and practical experience to take your ML workflow to the next level.

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I'm Emily Johnson, a passionate writer exploring the realms of literature and culture. Join me on a journey of creativity and discovery!
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