按照您自己的方式探索 Google Cloud 培训。
Google Cloud 提供 980 多项学习活动供您选择，我们设计的目录完整全面，充分考虑了您的需求。该目录包含各种可供您选择的活动形式，既有简短的单个实验，也有由视频、文档、实验和测验组成的多模块课程，您可以根据需求进行选择。我们的实验可为您提供实际云资源的临时凭据，以便您通过实际操作掌握 Google Cloud 知识。您可以跟踪、衡量和了解自己的 Google Cloud 学习进度，完成学习活动即可赢取徽章！
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实验 精选 Getting Started with Gaming on Cloud Spanner
In this lab, you will implement a player profile service and a game matchmaking service to work with Cloud Spanner.
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实验 精选 Building Batch Pipelines in Cloud Data Fusion
This lab will teach you how to use the Pipeline Studio in Cloud Data Fusion to build an ETL pipeline. Pipeline Studio exposes the building blocks and built-in plugins for you to build your batch pipeline, one node at a time. You will also use the Wrangler plugin to build and apply transformations to your data that…
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实验 精选 Set up a SIEM forwarder for Windows on Docker
In this lab, you configure a SIEM forwarder on a Windows VM using a standard Docker image. You use labels to add searchable metadata to the logs to optimize analytical capabilities.
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实验 精选 Online Data Migration to Cloud Spanner using Striim
In this lab you will learn how to migrate a Cloud SQL for MySQL database to Cloud Spanner using Google Cloud's data migration partner, Striim.
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实验 精选 Build and Configure an Integration using Application Integration
Learn the core concepts, functionalities, and best practices of Application Integration
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实验 精选 Tracking Cryptocurrency Exchange Trades with Google Cloud Platform in Real-Time
In this lab you will use Google Cloud services to help graph trades, volume, and time delta from trade execution to see any patterns in the high volatility of the cryptocurrency market.
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实验 精选 Deploying Spanner Applications with Cloud Functions and Cloud Run
In this lab, you write applications that utilize Spanner databases, and deploy them to both Cloud Functions and Cloud Run. You also install, configure, and enable the Spanner emulator for use in development environments.
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实验 精选 Modernizing Applications with Apigee X
In this lab, you deploy a backend service on Cloud Run. The backend service implements a REST API for a bank, storing customers, accounts, ATMs, and transactions in a Firestore database. You create a shared flow that retrieves and caches content from an external service. You then call that shared flow from your AP…
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实验 精选 Machine Learning with Spark on Google Cloud Dataproc
In this lab you will learn how to implement logistic regression using a machine learning library for Apache Spark running on a Google Cloud Dataproc cluster to develop a model for data from a multivariable dataset