The 10 best Google Cloud Platform courses in 2026

This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.

This is a Google Cloud Self-Paced Lab. In this lab, you will learn how to filter and sort data, and create looks with Looker.

This is a self-paced lab that takes place in the Google Cloud console. This hands-on lab shows you how to publish and consume messages with a pull subscriber, using the Google Cloud command line. Watch the short video <A HREF="https://youtu.be/oKU2wbTXMTY">Simplify Event Driven Processing with Cloud Pub/Sub</A>.

This is a self-paced lab that takes place in the Google Cloud console. This lab focuses on how to ingest new datasets into tables inside of BigQuery.

Cloud Dataprep is Google's self-service data preparation tool. In this lab, you will learn how to use Cloud Dataprep to clean and enrich multiple datasets using a mock use case scenario of customer info and purchase history.

This is a self-paced lab that takes place in the Google Cloud console. This lab demonstrates how optimization in your cluster's workloads can lead to an overall optimization of your resources and costs. It walks through a few different workload optimization strategies such as container-native load balancing, application load testing, readiness and liveness probes, and pod disruption budgets.

This is a self-paced lab that takes place in the Google Cloud console. This hands-on lab shows you how to create and deploy a Cloud Function using the Cloud Platform Console. Watch the short video Connect & Extend GCP Services with Google Cloud Functions.

"Microservices" describes a software design pattern in which an application is a collection of loosely coupled services. These services are fine-grained, and can be individually maintained and scaled. The microservices architecture is ideal for the public cloud, with its focus on elastic scaling with on-demand resources. In this course, you will learn how to build Java applications using Spring Boot and Spring Cloud on Google Cloud. You'll use Spring Cloud Config to manage your application's configuration. You'll send and receive messages with Pub/Sub and Spring Integration. You'll also use

This is the fourth course of a four-course series for cloud architects and engineers with existing AWS knowledge. It compares Google Cloud and AWS solutions and guides professionals on their use. This course focuses on deploying and monitoring applications in Google Cloud. The learners apply the knowledge of monitoring and application deployment processes in AWS to explore the differences with Google Cloud. Learners get hands-on practice building and managing Google Cloud resources.

This is a self-paced lab that takes place in the Google Cloud console. In this lab you’ll deploy and scale a Web App on Google Compute Engine.