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 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.