Using the Cloud SDK Command Line
Earned May 23, 2023 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned May 22, 2023 EDT
建構安全的 Google Cloud 網路
Earned Apr 15, 2023 EDT
在 Google Cloud 設定應用程式開發環境
Earned Apr 13, 2023 EDT
Google Cloud 必備知識
Earned Mar 23, 2023 EDT
Google Cloud 基礎知識：核心基礎架構
Earned Mar 12, 2023 EDT
本課程會介紹 Vertex AI Studio。您可以運用這項工具和生成式 AI 模型互動、根據商業構想設計原型，並投入到正式環境。透過身歷其境的應用實例、有趣的課程及實作實驗室，您將能探索從提示到正式環境的生命週期，同時學習如何將 Vertex AI Studio 運用在多模態版 Gemini 應用程式、提示設計、提示工程和模型調整。這個課程的目標是讓您能運用 Vertex AI Studio，在專案中發揮生成式 AI 的潛能。
了解详情
這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。
本課程介紹 Google Cloud 的 AI 和機器學習 (ML) 功能，著重說明如何開發生成式和預測式 AI 專案。我們也會探討「從資料到 AI」整個生命週期都適用的技術、產品和工具，並透過互動式練習，協助資料科學家、AI 開發人員和機器學習工程師精進專業知識。
了解详情
In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
了解详情
While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
For everyone using Google Cloud Platform for the first time, getting familar with gcloud, Google Cloud's command line, will help you get up to speed faster. In this quest, you'll learn how to install and configure Cloud SDK, then use gcloud to perform some basic operations like creating VMs, networks, using BigQuery, and using gsutil to perform operations.
Vertex AI Studio 簡介
Earned May 7, 2024 EDT
生成式 AI 簡介
Earned May 7, 2024 EDT
使用 BigQuery 進行機器學習
Earned Apr 12, 2024 EDT
Google Cloud 的 AI 和機器學習服務簡介
Earned Mar 5, 2024 EST
Build Batch Data Pipelines on Google Cloud
Earned Jan 8, 2024 EST
Build Streaming Data Pipelines on Google Cloud
Earned Jan 4, 2024 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned Jan 3, 2024 EST
透過 BigQuery 建構資料倉儲
Earned Dec 20, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Dec 19, 2023 EST
從 BigQuery 資料取得深入分析結果
Earned Nov 12, 2023 EST
在 Google Cloud 使用 Terraform 建構基礎架構
Earned Jun 24, 2023 EDT
建立 Google Cloud 網路
Earned Jun 17, 2023 EDT
在 Google Cloud 實作 Cloud 安全防護措施：基礎知識
Earned Jun 8, 2023 EDT
在 Compute Engine 導入 Cloud Load Balancing
Earned May 26, 2023 EDT
Using the Cloud SDK Command Line
Earned May 23, 2023 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned May 22, 2023 EDT
建構安全的 Google Cloud 網路
Earned Apr 15, 2023 EDT
在 Google Cloud 設定應用程式開發環境
Earned Apr 13, 2023 EDT
Google Cloud 必備知識
Earned Mar 23, 2023 EDT
Google Cloud 基礎知識：核心基礎架構
Earned Mar 12, 2023 EDT