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 VPC Flow Logs - Analyzing Network Traffic
In this lab, you configure a network to record traffic to and from an apache web server using VPC Flow Logs. You then export the logs to BigQuery to analyze them.
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实验 精选 Determine the difference between normal activity and an incident
Determine the difference between normal activity and an incident
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实验 精选 Mitigate Threats and Vulnerabilities with Security Command Center: Challenge Lab
In this lab, you test your Security Command Center skills by demonstrating your proficiency in creating mute rules, analyzing and fixing high vulnerability findings, identifying application vulnerabilities, and exporting Findings.
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实验 精选 Using the Natural Language API from Google Docs
In this hands-on lab, you use Apps Script to call the Natural Language API from Google Docs to analyze the sentiment of selected text in the document.
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实验 精选 Administering an AlloyDB Database
In this lab, you perform administrative tasks that are essential to the optimal use of an AlloyDB for PostgreSQL database.
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实验 精选 Speaking with a Webpage - Streaming Speech Transcripts
In this lab you take audio from the client's microphone and stream it to a Java servlet. The Java servlet passes the data to the Cloud Speech API, which then streams transcriptions back to the servlet.
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实验 精选 Introduction to APIs in Google Cloud
In this lab, you review the architecture and basic functioning of Application Programming Interfaces (APIs) and then practice by configuring and running Cloud Storage API methods in Cloud Shell.
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实验 精选 AlloyDB - Database Fundamentals
In this lab, you perform several key fundamental tasks for creating and managing AlloyDB for PostgreSQL instances and databases.
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实验 精选 Streamlining Wildlife Image Classification in BigQuery with an Imported Model
In this lab, you learn how to streamline an image classification workflow in BigQuery using an imported model (PyTorch model created in ONNX format), and Google SQL queries.