Discover Google Cloud training your way
With 980+ learning activities to choose from, Google Cloud has designed our comprehensive catalog with you in mind. The catalog consists of a variety of activity formats for you to pick from. Choose from bite-size individual labs or multi-module courses that consist of videos, documents, labs, and quizzes. Our labs give you temporary credentials to actual cloud resources, so you can learn Google Cloud using the real thing. Earn badges for what you complete, define, track, and measure your success with Google Cloud!
1051 results
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Lab Featured BigQuery Soccer Data Ingestion
Get started with sports data science by importing soccer data on matches, teams, players, and match events into BigQuery tables.
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Lab Featured BigQuery Machine Learning using Soccer Data
Learn how to use BigQuery ML with soccer shot data to create and use an expected goals model.
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Lab Featured APIs Explorer: Cloud SQL
In this lab, you will get hands-on practice with the Cloud SQL API and its associated methods by making calls through the APIs Explorer tool.
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Lab Featured Identify different batch and streaming data sources
Differentiate between batch and streaming data sources, formats, and frequency
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Lab Featured Introducing tcpdump
Let's introduce tcpdump and some of its features. We'll cover how to use tcpdump and what some of its flags do, as well as how to interpret the output. We will also practice saving packet captures to files and reading them back.
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Lab Featured Arcade Hero: Enter the Artifact Registry Maven
Arcade Hero: Artifact Registry Level One
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Lab Featured Translate Text with the Cloud Translation API
Cloud Translation translates an arbitrary string into any supported language. In this hands-on lab, you use the Cloud Translation API to detect the language of a text, and then translate the text.
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Lab Featured Connect to Cloud SQL from an Application in Google Kubernetes Engine
This lab shows how easy it is to connect an application in Google Kubernetes Engine to a Cloud SQL instance using the Cloud SQL Proxy container as a sidecar container. You will deploy a GKE cluster and a Cloud SQL Postgres instance and use the Cloud SQL Proxy container to allow communication between them.