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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1187 条结果
  1. 实验 精选

    Designing and Querying Bigtable Schemas

    In this lab, you explore a Bigtable instance and use the Bigtable CLI (cbt CLI) to query data in Bigtable. You also design a table schema and row key using best practices for Bigtable.

  2. 实验 精选

    Loading Data into Cloud SQL

    In this lab, you import data from CSV text files into Cloud SQL and then carry out some basic data analysis using simple queries.

  3. 实验 精选

    Arcade Hero: Enter the Artifact Registry Maven

    Arcade Hero: Artifact Registry Level One

  4. 实验 精选

    Cloud Scheduler: Qwik Start

    In this lab you'll create a recurring Cloud Scheduler job that specifies a Pub/Sub topic as the job target.

  5. 实验 精选

    Network Tiers - Optimizing Network Spend

    In this lab, you create one VM in the premium network service tier (default) and one VM in the standard network service tier. Then you compare the latency and routes for each VM instance.

  6. 实验 精选

    Understanding and Analyzing Your Costs with Google Cloud Billing Reports

    In this lab, you familiarize yourself with Google Cloud Billing reports, which provides built-in cost reporting for Google Cloud within the Google Cloud Console. You view Billing reports from a live billing account, understand current and forecasted Google Cloud costs, and then analyze costs using report filters t…

  7. 实验 精选

    Arcade Hero: Enter the Cloud Function Python

    Arcade Hero: Cloud Function Level One

  8. 实验 精选

    Generative AI: Go Hindi

    Arcade chatbot lab to learn about Hindi

  9. 实验 精选

    Create a Component Anomaly Detection Model using Visual Inspection AI

    In this lab, you will learn how to create a component anomaly detection model using Visual Inspection AI.

  10. 实验 精选

    It Speaks! Create Synthetic Speech Using Text-to-Speech

    In this lab, you create a series of audio files using the Text-to-Speech API, then listen to them to compare the differences.