On-demand activities
Google Cloud 根據您的需求規劃了全方位的課程內容，內含超過 980 項學習活動，並涵蓋多種活動型態，您可自由選擇。您可以選擇簡短的個別研究室，或是包含影片、文件、研究室和測驗的多單元課程。在研究室中，您可以透過臨時憑證實際使用雲端資源，直接累積 Google Cloud 實作經驗。完成課程可獲得徽章，讓您輕鬆掌握、追蹤及評估自己的 Google Cloud 學習成果！
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实验 精选 Predict Baby Weight with TensorFlow on Vertex AI
In this lab you train, evaluate, and deploy a machine learning model to predict a baby’s weight. You then send requests to the model to make online predictions. This lab is part of a series of labs on processing scientific data.
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实验 精选 Working with Artifact Registry
Artifact Registry is a single place to manage container images and language packages, and is fully integrated with Google Cloud tooling and and runtimes. This makes it simple to integrate it with your CI/CD tooling to set up automated pipelines.
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实验 精选 Preparing and Aggregating Data for Visualizations using Cloud Dataprep
Dataprep by Alteryx is Google's self-service data preparation tool built in collaboration with Alteryx. In this lab you will learn some more advanced techniques with Dataprep.
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实验 精选 Manage Multi-cluster Workloads at Scale with GKE Fleets and Teams
Provision and manage infrastructure resources for different teams with GKE Enterprise's fleet team management features
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实验 精选 Redacting Confidential Data within your Pipelines in Cloud Data Fusion
In this lab you wil learn how to use the Cloud Data Fusion plugin for Cloud DLP to redact sensitive data.
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实验 精选 Exploring the Lineage of Data with Cloud Data Fusion
This lab shows how to use Cloud Data Fusion to explore data lineage - the data's origins and its movement over time.
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实验 精选 Implement Load Balancing on Compute Engine：挑戰研究室
完成 Implement Load Balancing on Compute Engine 技能徽章課程的研究室之後，您可以透過這個挑戰研究室檢測所學的技能與知識。進行這個研究室之前，請先熟悉研究室的內容。
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实验 精选 Cloud Composer：複製不同位置的 BigQuery 資料表
在本實驗室中，您要在 Cloud Composer 建立並執行 Apache Airflow 工作流程，從位於美國 Cloud Storage bucket 內的 BigQuery 資料集，將資料表匯出至歐盟地區的 bucket，接著將這些資料表匯入歐盟地區的 BigQuery 資料集。
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实验 精选 Rent-a-VM to Process Earthquake Data
In this lab you spin up a virtual machine, configure its security, access it remotely, and then carry out the steps of an ingest-transform-and-publish data pipeline manually. This lab is part of a series of labs on processing scientific data.