Grow with Google

In this comprehensive course, you will learn to identify and use fundamental technologies for effective MLOps, adopt best CI/CD practices in the context of ML systems, and configure Google Cloud architectures for reliable MLOps environments. Gain the skills to implement reliable and repeatable training and inference workflows, and continuously improve deployed models.

Machine Learning Operations (MLOps): Getting Started

Learn the fundamentals of MLOps and its importance in the deployment and management of ML systems.

Introduction to MLOps

Explore best practices for continuous integration and continuous deployment in the context of machine learning.

CI/CD for Machine Learning

Understand how to configure and provision Google Cloud architectures for effective MLOps environments.

Google Cloud Architectures for MLOps

Implement reliable and repeatable workflows for training and inference in production environments.

Reliable Training and Inference Workflows

This course introduces participants to the essential tools and best practices of MLOps for implementing, evaluating, and operating production ML systems on Google Cloud. Enhance your cloud career by mastering MLOps skills and earning a badge to showcase your expertise.

Professionals looking to implement, evaluate, and operate production ML systems on Google Cloud.

Machine Learning Engineers

Individuals who develop models and want to enhance their deployment speed and rigor.

Data Scientists

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Machine Learning Operations (MLOps): Getting Started

Overview

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