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ARJUN RAGHUNANDANAN

成为会员时间：2020

黄金联赛

33105 积分
探索生成式 AI - Vertex AI Earned Sep 15, 2024 EDT
使用 Gemini 和 Streamlit 開發生成式 AI 應用程式 Earned Sep 12, 2024 EDT
使用 Gemini：端對端 SDLC Earned Sep 11, 2024 EDT
使用 Gemini：DevOps 工程師 Earned Sep 11, 2024 EDT
使用 Gemini：資安工程師 Earned Sep 11, 2024 EDT
使用 Gemini：網路工程師 Earned Sep 11, 2024 EDT
使用 Gemini：數據資料學家和分析師 Earned Sep 10, 2024 EDT
使用 Gemini：雲端架構師 Earned Sep 10, 2024 EDT
使用 Gemini：應用程式開發人員 Earned Sep 5, 2024 EDT
在 Vertex AI 設計提示 Earned Sep 5, 2024 EDT
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則 Earned Sep 4, 2024 EDT
負責任的 AI 技術簡介 Earned Sep 3, 2024 EDT
大型語言模型簡介 Earned Sep 3, 2024 EDT
生成式 AI 簡介 Earned Sep 3, 2024 EDT
[DEPRECATED] Secure Workloads in Google Kubernetes Engine Earned Jun 4, 2021 EDT
Google Kubernetes Engine Best Practices: Security Earned Jun 4, 2021 EDT
Google Kubernetes Engine 成本效益最佳化 Earned Jun 1, 2021 EDT
透過 Google Cloud Observability 監控及記錄系統狀態 Earned Nov 15, 2020 EST
DEPRECATED Google Cloud's Operations Suite Earned Nov 15, 2020 EST
使用 BigQuery ML 為預測模型進行資料工程 Earned Nov 5, 2020 EST
[DEPRECATED] Data Engineering Earned Nov 5, 2020 EST
在 Google Cloud 使用機器學習 API Earned Nov 4, 2020 EST
Machine Learning APIs Earned Nov 2, 2020 EST
在 Google Cloud 為機器學習 API 準備資料 Earned Nov 1, 2020 EST
DEPRECATED Explore Machine Learning Models with Explainable AI Earned Oct 31, 2020 EDT
基本概念：資料、機器學習和 AI Earned Oct 31, 2020 EDT
Website on Google Cloud Earned Oct 31, 2020 EDT
設定 Google Cloud 網路 Earned Oct 27, 2020 EDT
透過 Google Cloud 建構網站 Earned Oct 15, 2020 EDT
在 Google Cloud 部署 Kubernetes 應用程式 Earned Oct 14, 2020 EDT
在 Google Cloud 設定應用程式開發環境 Earned Oct 13, 2020 EDT
在 Compute Engine 導入 Cloud Load Balancing Earned Oct 13, 2020 EDT
建構安全的 Google Cloud 網路 Earned Oct 12, 2020 EDT
[DEPRECATED] Build Interactive Apps with Google Assistant Earned Oct 12, 2020 EDT
從 BigQuery 資料取得深入分析結果 Earned Oct 12, 2020 EDT
建立 Google Cloud 網路 Earned Sep 14, 2020 EDT
Cloud Logging Earned Sep 14, 2020 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant Earned Sep 14, 2020 EDT
DevOps Essentials Earned Sep 13, 2020 EDT
DEPRECATED Cloud Architecture Earned Sep 13, 2020 EDT
Google Developer Essentials Earned Sep 13, 2020 EDT
DEPRECATED BigQuery Basics for Data Analysts Earned Sep 12, 2020 EDT
NCAA® March Madness®: Bracketology with Google Cloud Earned Sep 11, 2020 EDT
Google Cloud 中的 Kubernetes Earned Sep 11, 2020 EDT
DEPRECATED Applied Data: Blockchain Earned Sep 11, 2020 EDT
雲端工程 Earned Sep 9, 2020 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network Earned Sep 8, 2020 EDT
基本概念：基礎架構 Earned Aug 28, 2020 EDT
Google Workspace Essentials Earned Aug 28, 2020 EDT
Google Cloud Essentials Earned Aug 27, 2020 EDT

探索生成式 AI - Vertex AI 課程包含一系列實驗室，幫助您瞭解 如何在 Google Cloud 使用生成式 AI。透過實驗室，您將瞭解 如何使用 Vertex AI PaLM API 系列模型，包括 text-bison、chat-bison、 和 textembedding-gecko。您也會瞭解提示設計、最佳做法、 以及這些模型如何用於構思、文字分類、文字擷取、文字 摘要等。您也會瞭解如何透過 Vertex AI 自訂訓練功能調整基礎模型， 並將模型部署至 Vertex AI 端點。

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完成 使用 Gemini 和 Streamlit 開發生成式 AI 應用程式 技能徽章中階課程，即可證明您具備下列技能： 生成文字、透過 Python SDK 和 Gemini API 呼叫函式，以及運用 Cloud Run 部署 Streamlit 應用程式。 您將瞭解如何以不同方式透過提示請 Gemini 生成文字、使用 Cloud Shell 測試及疊代 Streamlit 應用程式，隨後封裝成 Docker 容器並在 Cloud Run 中部署。

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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助您透過 Google Cloud 使用 Google 產品和服務，開發、測試、部署及管理應用程式。有了 Gemini 的協助，您會學到如何開發和建構網頁應用程式、修正應用程式中的錯誤、開發測試及查詢資料。在實作研究室中，您也會體驗到 Gemini 如何改良軟體開發生命週期 (SDLC)。 Duet AI 已更名為 Gemini，這是我們的新一代模型。

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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助工程師透過 Google Cloud 管理基礎架構。您將學到如何透過提示讓 Gemini 尋找和瞭解應用程式記錄檔、建立 GKE 叢集，以及研究如何打造建構環境。在實作研究室中，您也會瞭解 Gemini 如何改良開發運作的工作流程。 Duet AI 已更名為 Gemini，是我們新一代的模型。

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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助您透過 Google Cloud 保護雲端環境和資源。您將學到如何將工作負載範例部署到 Google Cloud 中的環境，以及運用 Gemini 找出並修復安全性設定錯誤。在實作研究室中，您也會體驗到 Gemini 如何改良雲端安全防護機制。 Duet AI 已更名為 Gemini，這是我們的新一代模型。

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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助網路工程師建立、更新及維護虛擬私有雲網路。您將瞭解如何透過提示讓 Gemini 為網路工作提供指引，獲得比搜尋結果更具體的資訊。在實作研究室中，您也會體驗到 Gemini 如何簡化 Google Cloud 虛擬私有雲網路的作業。 Duet AI 已更名為 Gemini，這是我們的新一代模型。

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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助分析客戶資料及預測產品銷售情形。您也會學習如何在 BigQuery 中使用客戶資料識別、分類及開發新客戶。透過使用實作研究室，您可以體驗 Gemini 如何改良資料分析和機器學習工作流程。 Duet AI 已更名為 Gemini，這是我們的新一代模型。

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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助管理員在 Google Cloud 佈建基礎架構。您將瞭解如何透過提示讓 Gemini 解釋基礎架構、部署 GKE 叢集，以及更新既有的基礎架構。在實作研究室中，您也會體驗到 Gemini 如何改良 GKE 的部署工作流程。 Duet AI 已更名為 Gemini，這是我們的新一代模型。

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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助開發人員透過 Google Cloud 建構應用程式。您將瞭解如何透過提示讓 Gemini 為您解釋程式碼內容、推薦 Google Cloud 服務，以及生成應用程式的程式碼。在實作研究室中，您也會體驗到 Gemini 如何改良應用程式的開發工作流程。 Duet AI 已更名為 Gemini，這是我們的新一代模型。

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完成 在 Vertex AI 設計提示 技能徽章入門課程，即可證明您具備下列技能： 在 Vertex AI 設計提示、分析圖片，以及運用多模態模型生成內容。瞭解如何建立有效的提示、引導生成式 AI 輸出內容， 以及將 Gemini 模型用於實際的行銷情境。

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隨著企業持續擴大使用人工智慧和機器學習，以負責任的方式發展相關技術也日益重要。對許多企業來說，談論負責任的 AI 技術可能不難，如何付諸實行才是真正的挑戰。如要瞭解如何在機構中導入負責任的 AI 技術，本課程絕對能助您一臂之力。 您可以從中瞭解 Google Cloud 目前採取的策略、最佳做法和經驗談，協助貴機構奠定良好基礎，實踐負責任的 AI 技術。

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這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性，以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。

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這是一堂入門級的微學習課程，旨在探討大型語言模型 (LLM) 的定義和用途，並說明如何調整提示來提高 LLM 成效。此外，也會介紹多項 Google 工具，協助您自行開發生成式 AI 應用程式。

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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。

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Earn a skill badge by completing the Secure Workloads in Google Kubernetes Engine quest, where you learn about security at scale on Google Kubernetes Engine (GKE) including how to: migrate containers from virtual machines to Google Kubernetes Engine, restrict network connections in GKE using firewalls and Network Policies, use role-based access controls (RBAC) in GKE, use Binary Authorization for security controls of your images, secure applications in GKE using 3 access levels: host, network, Kubernetes API, and harden GKE cluster configurations. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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Get Anthos Ready. This Google Kubernetes Engine-centric quest of best practice hands-on labs focuses on security at scale when deploying and managing production GKE environments -- specifically role-based access control, hardening, VPC networking, and binary authorization.

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完成 Google Kubernetes Engine 成本效益最佳化 技能徽章中階課程， 即可證明您具備下列技能：建立及管理多租戶叢集、依據命名空間監控資源使用量、 設定自動調度叢集和 Pod 資源以提升效能、設定負載平衡以最佳化 資源分配，以及導入有效性和完備性探測，確保應用程式維持健康並符合成本效益。

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完成 透過 Google Cloud Observability 監控及記錄系統狀態 技能徽章入門課程， 即可證明您具備下列技能：監控 Compute Engine 中的虛擬機器、 運用 Cloud Monitoring 監管多項專案、在 Cloud Functions 延伸應用監控和記錄功能、 建立和傳送自訂應用程式指標，以及根據自訂指標設定 Cloud Monitoring 快訊。

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Learn the ins and outs of Google Cloud's operations suite, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. These labs will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the challenge lab at the end of the Monitor and Log with Google Cloud Operations Suite to receive an exclusive Google Cloud digital badge.

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完成使用 BigQuery ML 為預測模型進行資料工程技能徽章中階課程， 即可證明自己具備下列知識與技能：運用 Dataprep by Trifacta 建構連至 BigQuery 的資料轉換 pipeline； 使用 Cloud Storage、Dataflow 和 BigQuery 建構「擷取、轉換及載入」(ETL) 工作負載， 以及使用 BigQuery ML 建構機器學習模型。

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This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.

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完成「在 Google Cloud 使用機器學習 API」課程，即可獲得進階技能徽章。本課程說明以下機器學習和 AI 技術的基本功能： Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。

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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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完成 在 Google Cloud 為機器學習 API 準備資料 技能徽章入門課程，即可證明您具備下列技能： 使用 Dataprep by Trifacta 清理資料、在 Dataflow 執行資料管道、在 Dataproc 建立叢集和執行 Apache Spark 工作，以及呼叫機器學習 API，包含 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。

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Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest and the final assessment challenge lab to receive a skill badge that you can share with your network.

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大數據、機器學習和人工智慧 (AI) 是時下熱門的 電腦相關話題，但這些領域相當專業，就算想要入門 也難以取得教材或資料。幸好，Google Cloud 提供了此領域的多種服務，而且容易使用。 參加這堂入門課程，您就能踏出第一步， 開始學習運用 BigQuery、Cloud Speech API 以及 Video Intelligence 等工具。

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In this quest you will learn about the four Google Cloud website architectures available to ensure that your website is available and scalable. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional challenge lab at the end of this Build a Website on Google Cloud to receive an exclusive Google Cloud digital badge. This quest is based on the video series Get Cooking in Cloud.

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完成「設定 Google Cloud 網路」課程，即可獲得技能徽章。 您將瞭解如何在 Google Cloud Platform 執行基本的網路工作，包括建立自訂網路、新增子網路防火牆規則，還有建立 VM 並測試 VM 之間的通訊延遲。

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完成透過 Google Cloud 建構網站技能徽章課程，即可獲得入門級技能徽章。 本課程以 Get Cooking in Cloud 系列影片為基礎， 涵蓋以下主題：在 Cloud Run 部署網站在 Compute Engine 託管網頁應用程式在 Google Kubernetes Engine 建立、 部署及擴充網站使用 Cloud Build 將單體式應用程式遷移至微服務架構

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完成 在 Google Cloud 部署 Kubernetes 應用程式 技能徽章中階課程，即可證明您具備下列技能： 設定及建構 Docker 容器映像檔、建立及管理 Google Kubernetes Engine (GKE) 叢集、運用 kubectl 有效 管理叢集，以及運用強大的持續推送軟體更新做法來部署 Kubernetes 應用程式。

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只要修完「在 Google Cloud 設定應用程式開發環境」課程，就能獲得技能徽章。 在本課程中，您將學會如何使用以下技術的基本功能，建構和連結以儲存空間為中心的雲端基礎架構：Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。

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完成「在 Compute Engine 導入 Cloud Load Balancing」技能徽章入門課程，即可證明您具備下列技能： 在 Compute Engine 建立及部署虛擬機器， 以及設定網路和應用程式負載平衡器。

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完成「建構安全的 Google Cloud 網路」課程，即可獲得技能徽章。本課程將說明多項網路相關 資源，協助您在 Google Cloud 建構、調度資源和保護應用程式。

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Earn a skill badge by completing the Build Interactive Apps with Google Assistant quest, where you will learn how to build Google Assistant applications, including how to: create an Actions project, integrate Dialogflow with an Actions project, test your application with Actions simulator, build an Assistant application with flash cards template, integrate customer MP3 files with your Assistant application, add Cloud Translation API to your Assistant application, and use APIs and integrate them into your applications. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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完成 從 BigQuery 資料取得深入分析結果 技能徽章入門課程，即可證明您具備下列技能： 撰寫 SQL 查詢、查詢公開資料表、將樣本資料載入 BigQuery、使用 BigQuery 的查詢驗證工具 排解常見語法錯誤，以及在 Looker Studio 中 透過連結 BigQuery 資料建立報表。

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完成 建立 Google Cloud 網路 課程即可獲得技能徽章。這個課程將說明 部署及監控應用程式的多種方法，包括查看 IAM 角色及新增/移除 專案存取權、建立虛擬私有雲網路、部署及監控 Compute Engine VM、編寫 SQL 查詢、在 Compute Engine 部署及監控 VM，以及 使用 Kubernetes 透過多種方法部署應用程式。

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Cloud Logging is a fully managed service that performs at scale. It can ingest application and system log data from thousands of VMs and, even better, analyze all that log data in real time. In this fundamental-level Quest, you learn how to store, search, analyze, monitor, and alert on log data and events from Google Cloud. The labs in the Quest give you hands-on practice using Cloud Logging to maximize your learning experience and provide insight on how you can use Cloud Logging to your own Google Cloud environment.

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With Google Assistant part of over a billion consumer devices, this quest teaches you how to build practical Google Assistant applications integrated with Google Cloud services via APIs. Example apps will use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks. You will build 5 different applications that explore useful and fun tools you can extend on your own. No hardware required! These labs use the cloud-based Google Assistant simulator environment for developing and testing, but if you do have your own device, such as a Google Home or a Google Hub, additional instructions are provided on how to deploy your apps to your own hardware.

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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this course you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out!

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.

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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.

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Kubernetes 是最受歡迎的容器自動化調度管理系統，Google Kubernetes Engine 則專門支援 Google Cloud 中的 代管 Kubernetes 部署項目。這門進階課程將帶您實際練習設定 Docker 映像檔和容器，並部署完整的 Kubernetes Engine 應用程式。 您會學到如何將容器自動化調度管理機制， 整合到自己的工作流程，這些技巧相當實用。 想透過實作挑戰實驗室展現 技能、驗收學習成果嗎？本課程結束後，再完成 在 Google Cloud 部署 Kubernetes 應用程式課程 結尾的挑戰實驗室，即可獲得專屬 Google Cloud 數位徽章。

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Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.

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本入門課程有別於其他課程。 透過這些實驗室，IT 專業人員將有機會實際練習， 熟悉出現在 Google Cloud 助理雲端工程師認證中的主題和服務。本課程包含多個專門的實驗室，從 IAM、網路建立 到 Kubernetes Engine 部署作業， 可全面驗收您的 Google Cloud 知識。請注意，雖然進行這些 實驗室可提升您的技能和能力，但仍建議同時詳閱 測驗指南和其他可用的準備資源。

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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.

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如果您是剛起步的雲端開發人員， 想在 Google Cloud Essentials 外獲得更多實作經驗，歡迎參加本課程。您將透過實作實驗室， 深入瞭解 Cloud Storage 和其他重要應用程式服務，例如： Monitoring 和 Cloud Functions。您將習得 在任何 Google Cloud 專案都適用的寶貴技能。

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Workspace is Google's collaborative applications platform, delivered from Google Cloud. In this introductory-level course you will get hands-on practice with Workspace’s core applications from a user perspective. Although there are many more applications and tool components to Workspace than are covered here, you will get experience with the primary apps: Gmail, Calendar, Sheets and a handful of others. Each lab can be completed in 10-15 minutes, but extra time is provided to allow self-directed free exploration of the applications.

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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.

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