按需活动

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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1056 条结果

  1. 实验 精选

    Scaling Microservices Applications: Migration to Redis Enterprise on Google Cloud

    In this lab, you will deploy a fully functioning microservices e-Commerce website application on Google Cloud using Redis to run the shopping cart service and then migrate that to Redis Enterprise for scalability and high availability.

  2. 实验 精选

    Google Cloud 實作研究室導覽

    在第一個實作研究室中,您會存取 Google Cloud 控制台並使用下列 Google Cloud 基本功能:專案、資源、IAM 使用者、角色、權限和 API。

  3. 实验 精选

    Create and Manage AlloyDB Instances: Challenge Lab

    This challenge lab tests your ability to create and manage AlloyDB instances and databases on Google Cloud.

  4. 实验 精选

    Dataplex: Qwik Start - Command Line

    This lab shows you how to get started with Dataplex using the command line by walking you through creating a lake, adding a zone, attaching and detaching assets, and deleting zones and lakes.

  5. 实验 精选

    Pub/Sub:Qwik Start - Python

    在本研究室中,您將瞭解 Pub/Sub 的基本知識、如何使用 Python 指令碼建立主題和訂閱者,以及發布和查看訊息。詳情請觀看短片:《透過 Cloud Pub/Sub 簡化事件導向處理作業》。

  6. 实验 精选

    Use reports to remediate findings

    Remediate threats detailed in a management report

  7. 实验 精选

    Optical Character Recognition (OCR) with Document AI (Python)

    In this lab, you will learn how to perform Optical Character Recognition using the Document AI API with Python.

  8. 实验 精选

    Summarize Text using SQL and LLMs in BigQuery ML

    In this lab, you will explore how to perform summarization of source code from GitHub repos and identification of the language of programming in the repo, using Vertex AI Large Language Model (LLM) for text generation.

  9. 实验 精选

    Form Parsing with Document AI (Python)

    In this lab, you will learn how to use the Document AI Form Parser to parse a handwritten form with Python.

  10. 实验 精选

    Exploring NCAA Data with BigQuery

    Use BigQuery to explore the NCAA dataset of basketball games, teams, and players. The data covers plays from 2009 and scores from 1996. Watch How the NCAA is using Google Cloud to tap into decades of sports data.