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！
42 条结果
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实验 精选 Running a Containerized App on Google Kubernetes Engine
Containers are becoming a popular way to run and scale applications across multiple cloud providers or on both cloud and on premise hardware. This lab provides a quick introduction to running a website on Google Container Engine using Docker.
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实验 精选 Introduction to Cloud Bigtable (Java)
Learn how to avoid common mistakes with schema design, import data in a sequence file, and query your data using Cloud Bigtable with the Java HBase client.
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实验 精选 Introduction to Dart
In this lab you will learn the basics of Dart. Understand how to work with variables, flow control and functions to start your journey with Dart.
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实验 精选 Introduction to Cloud Dataproc: Hadoop and Spark on Google Cloud
In this lab, you will learn how to start a managed Spark/Hadoop cluster using Dataproc, submit a sample Spark job, and shut down your cluster using the Google Cloud Console.
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实验 精选 VM Migration: Introduction to StratoZone Assessments
In this lab you'll learn how to assess an IT environment with StratoZone's scalable discovery.
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实验 精选 Introduction to Migration Center Assessments
Learn how to assess a customer's existing environment, collect information from a supported database as well as import data collected from Azure/AWS infrastructure. Generate inventory, cloud fit score, and financial reports including TCO and ROI analysis.
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实验 精选 Gemini 函式呼叫簡介
在本研究室中，您會瞭解如何搭配使用 Vertex AI Gemini API 和 Python 適用的 Vertex AI SDK，透過 Gemini Pro (gemini-pro) 模型發出函式呼叫。
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课程 精选 Getting Started with Google Kubernetes Engine - 繁體中文
歡迎參加「開始使用 Google Kubernetes Engine」課程。Kubernetes 是位於應用程式和硬體基礎架構之間的軟體層。如果您對這項技術感興趣，這堂課程可以滿足您的需求。有了 Google Kubernetes Engine，您就能在 Google Cloud 中以代管服務的形式使用 Kubernetes。 本課程的目標在於介紹 Google Kubernetes Engine (常簡稱為 GKE) 的基本概念，以及如何將應用程式容器化，以便在 Google Cloud 中執行。課程首先會初步介紹 Google Cloud，隨後簡介容器、Kubernetes、Kubernetes 架構和 Kub…
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课程 精选 Launching into Machine Learning
The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a …
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课程 精选 TensorFlow on Google Cloud
This course covers designing and building a TensorFlow input data pipeline, building ML models with TensorFlow and Keras, improving the accuracy of ML models, writing ML models for scaled use, and writing specialized ML models.