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Nithya Santhoshini

Member since 2022

Gold League

53830 points
Qwiklabs Trivia December 2023 Week 2 Earned Dec 11, 2023 EST
Qwiklabs Trivia December 2023 Week 1 Earned Dec 11, 2023 EST
Qwiklabs Trivia August 2023 Earned Aug 28, 2023 EDT
使用 Google Data Cloud 共用資料 Earned Aug 16, 2023 EDT
透過 BigQuery 建構資料倉儲 Earned Aug 16, 2023 EDT
使用 Document AI 大規模自動擷取資料 Earned Aug 15, 2023 EDT
實現 Cloud Storage 和數據保護解決方案 Earned Aug 14, 2023 EDT
開始使用 Looker Earned Aug 14, 2023 EDT
使用 Eventarc 建構事件導向應用程式 Earned Aug 14, 2023 EDT
使用 API Gateway 部署及保護無伺服器 API Earned Aug 12, 2023 EDT
使用 AppSheet 建構應用程式 Earned Aug 11, 2023 EDT
在 Cloud Storage 建立串流資料湖泊 Earned Aug 11, 2023 EDT
Level 2: Apps Script and Networks Earned Aug 10, 2023 EDT
使用 BigQuery ML 為預測模型進行資料工程 Earned Aug 10, 2023 EDT
[DEPRECATED] Data Engineering Earned Aug 10, 2023 EDT
使用 Apps Script 整合 BigQuery 資料與 Google Workspace Earned Aug 10, 2023 EDT
DEPRECATED BigQuery Basics for Data Analysts Earned Aug 10, 2023 EDT
使用預訓練 API 實現語音和語言解決方案 Earned Aug 10, 2023 EDT
透過 Google Cloud Observability 監控及記錄系統狀態 Earned Aug 10, 2023 EDT
Google Cloud 監控工具 Earned Aug 9, 2023 EDT
從 BigQuery 資料取得深入分析結果 Earned Aug 9, 2023 EDT
以串流方式將分析資料傳入 BigQuery Earned Aug 9, 2023 EDT
監控及管理 Google Cloud 資源 Earned Aug 9, 2023 EDT
在 Google Cloud 儲存、處理與管理資料 - 控制台 Earned Aug 9, 2023 EDT
使用 Dataplex 整理及管理資料 Earned Aug 8, 2023 EDT
在 Cloud Storage 建立安全的資料湖泊 Earned Aug 8, 2023 EDT
在 Google Cloud 使用機器學習 API Earned Aug 8, 2023 EDT
使用 Cloud Run functions 建構無伺服器應用程式 Earned Aug 8, 2023 EDT
Level 3: GenAI Earned Aug 8, 2023 EDT
使用 Cloud Vision API 分析圖片 Earned Aug 8, 2023 EDT
Vertex AI Studio 簡介 Earned Aug 4, 2023 EDT
建立圖像說明生成模型 Earned Aug 4, 2023 EDT
Transformer 和 BERT 模型 Earned Aug 4, 2023 EDT
注意力機制 Earned Aug 4, 2023 EDT
編碼器-解碼器架構 Earned Aug 4, 2023 EDT
圖像生成簡介 Earned Aug 4, 2023 EDT
Generative AI Fundamentals - 繁體中文 Earned Aug 4, 2023 EDT
負責任的 AI 技術簡介 Earned Aug 4, 2023 EDT
大型語言模型簡介 Earned Aug 4, 2023 EDT
生成式 AI 簡介 Earned Aug 4, 2023 EDT
充實中繼資料及發掘 Lakehouse 資料 Earned Jul 31, 2023 EDT
保護 Lakehouse 資料 Earned Jul 31, 2023 EDT
在 Google Cloud 實作 Sensitive Data Protection Earned Jul 31, 2023 EDT
Level 2: Data Deep Dive Earned Jul 31, 2023 EDT
Qwiklabs Trivia July 2023 Earned Jul 30, 2023 EDT
Level 1: AppDev and Infrastructure Earned Jul 29, 2023 EDT
DEPRECATED Networking Fundamentals on Google Cloud Earned Jul 29, 2023 EDT
Getting Started with Go on Google Cloud Earned Jul 29, 2023 EDT
Google Cloud Compute 基本操作 Earned Jul 29, 2023 EDT
在 Google App Engine 上部署及管理應用程式 Earned Jul 29, 2023 EDT
DEPRECATED IoT in the Google Cloud Earned Jul 2, 2022 EDT
運用 Cloud Run 開發無伺服器應用程式 Earned Jul 1, 2022 EDT
Google Cloud Run Serverless Workshop Earned Jul 1, 2022 EDT
Workspace: Add-ons Earned Jun 28, 2022 EDT
DEPRECATED Exploring APIs Earned Jun 28, 2022 EDT
[DEPRECATED] Build Interactive Apps with Google Assistant Earned Jun 27, 2022 EDT
使用 Firebase 開發無伺服器應用程式 Earned Jun 27, 2022 EDT
Build Apps & Websites with Firebase Earned Jun 27, 2022 EDT
透過 Google Cloud 建構網站 Earned Jun 27, 2022 EDT
透過 Google Cloud 建構網站 Earned Jun 27, 2022 EDT
Cloud Development Earned Jun 25, 2022 EDT
Baseline: Deploy & Develop Earned Jun 22, 2022 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant Earned Jun 22, 2022 EDT
Google 開發人員必備知識 Earned Jun 21, 2022 EDT
Google Cloud Solutions I: Scaling Your Infrastructure Earned Jun 17, 2022 EDT
DEPRECATED Google Cloud's Operations Suite Earned Jun 17, 2022 EDT
瞭解 Google Cloud 費用 Earned Jun 17, 2022 EDT
在 Google Cloud 實作 DevOps 工作流程 Earned Jun 16, 2022 EDT
在 Google Cloud 部署 Kubernetes 應用程式 Earned Jun 16, 2022 EDT
建立 Google Cloud 網路 Earned Jun 16, 2022 EDT
DevOps 必備知識 Earned Jun 16, 2022 EDT
DEPRECATED Cloud Architecture Earned Jun 16, 2022 EDT
Google Cloud 中的 Kubernetes Earned Jun 16, 2022 EDT
雲端工程 Earned Jun 16, 2022 EDT
建構安全的 Google Cloud 網路 Earned Jun 15, 2022 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network Earned Jun 14, 2022 EDT
在 Google Cloud 設定應用程式開發環境 Earned Jun 13, 2022 EDT
基本概念:基礎架構 Earned Jun 13, 2022 EDT
在 Compute Engine 導入 Cloud Load Balancing Earned Jun 13, 2022 EDT
Google Cloud 必備知識 Earned Jun 1, 2022 EDT

Hey there! You're invited to game on with Qwiklabs Trivia for December 2023! Play throughout the month and boost your cloud learning journey. This week, we're releasing a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the December week 2 badge!

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Hey there! You're invited to game on with Qwiklabs Trivia for December 2023! Play throughout the month and boost your cloud learning journey. This week, we're releasing a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the December week 1 badge!

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Welcome to Qwiklabs Trivia for August! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands-on experience on GCP and partner services and earn the August badge.

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完成「使用 Google Data Cloud 共用資料」課程,即可獲得技能徽章。 在本課程中,您會透過 Google Cloud 資料共用合作夥伴, 使用專屬資料集進行數據分析, 獲得豐富的實務經驗。客戶訂閱這類資料後,即可在自家平台查詢, 並用自己的資料集補強。此外,也能使用圖表 工具,打造客戶專用的資訊主頁。

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完成 透過 BigQuery 建構資料倉儲 技能徽章中階課程,即可證明您具備下列技能: 彙整資料以建立新資料表、排解彙整作業問題、利用聯集附加資料、建立依日期分區的資料表, 以及在 BigQuery 使用 JSON、陣列和結構體。

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完成使用 Document AI 大規模自動擷取資料課程,即可獲得入門級技能徽章。在本課程中,您將瞭解如何使用 Document AI 擷取、處理及提取資料。

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若想獲得技能徽章,請完成實現 Cloud Storage 和數據保護解決方案 技能徽章課程,您將在此瞭解如何建立 Cloud Storage bucket、 如何使用 Cloud Storage 指令列,以及如何在區塊中使用值區鎖定功能保護物件。

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完成「開始使用 Looker」技能徽章課程,即可獲得技能徽章, 您將從中瞭解如何使用 Looker Studio 和 Looker 分析、呈現及整理資料。

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完成「使用 Eventarc 建構事件導向應用程式」課程,即可獲得技能徽章。 在本課程中,您將使用 Eventarc 為不同資源 (包括 Pub/Sub 主題和 Cloud Storage bucket) 建立事件觸發條件。

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完成「使用 API Gateway 部署及保護無伺服器 API」課程,即可獲得技能徽章。 本課程將說明如何使用 API Gateway,透過全代管閘道部署、保護及管理 API。

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完成使用 AppSheet 建構應用程式課程,即可獲得技能徽章 ,瞭解如何使用 AppSheet 建構、設定及發布應用程式。

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完成「在 Cloud Storage 建立串流資料湖泊」任務,即可獲得技能徽章。 本課程中,您將綜合運用 Pub/Sub、Dataflow 和 Cloud Storage, 在 Google Cloud 建立串流資料湖泊。

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For organisations to thrive in the digital world, it is important for them to have secured networks to protect sensitive data, prevent cyber threats and maintain customer trust. Learn the principles of network design, security and management and integrating BigQuery Data and Google Workspace using Apps Script. Gain hands-on experience with labs carefully designed to nurture and assess your tech skills and set you on a course to earn your first Google Cloud credential.

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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「使用 Apps Script 整合 BigQuery 資料與 Google Workspace」技能徽章入門課程,即可證明您瞭解如何透過 AppSheet 將 Workspace 產品連結至 BigQuery。

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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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完成使用預訓練 API 實現語音和語言解決方案課程以獲得技能徽章,了解如何使用與語音相關的 API 工具來合成和轉錄語音。

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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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完成「Google Cloud 監控工具」技能徽章入門課程, 即可證明您具備下列技能:使用 Cloud Monitoring 工具監控 Google Cloud 資源。

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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 Data Studio 中 透過連結 BigQuery 資料建立報表。

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完成「以串流方式將分析資料傳入 BigQuery」課程,即可獲得技能徽章。 在此課程中,您將綜合應用 Pub/Sub、Dataflow 和 BigQuery,並以串流方式傳送 資料進行分析。

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完成「監控及管理 Google Cloud 資源」技能徽章入門課程,即可證明您具備下列技能:授予及撤銷 IAM 權限; 安裝 Monitoring 和 Logging 代理程式;建立、部署及測試事件導向的 Cloud Run 函式。

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Cloud Storage、Cloud Functions 和 Cloud Pub/Sub 都是 Google Cloud Platform 服務, 可用於儲存、處理及管理資料。您可以整合運用這三種服務, 打造各式各樣的資料導向應用程式。在這個技能徽章課程中, 您將使用 Cloud Storage 儲存圖片、透過 Cloud Functions 處理, 並利用 Cloud Pub/Sub 將圖片傳送至其他應用程式。

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完成「使用 Dataplex 整理及管理資料」技能徽章入門課程,即可證明您具備下列技能:建立 Dataplex 資產、建立切面類型,以及將切面套用至 Dataplex 中的項目。 技能徽章課程透過實作實驗室和挑戰評量,檢驗學員對於特定產品的實作知識。 完成課程或直接進行挑戰實驗室,即可取得徽章。徽章可證明您的專業能力、提升專業形象,開創更多職涯發展機會。前往個人資料頁面,追蹤您獲得的徽章。

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完成「在 Cloud Storage 建立安全的資料湖泊」技能徽章入門課程,即可證明您具備下列技能: 保護及設定 Cloud Storage bucket、使用 Gemini 生成文字、管理 IAM 存取控管機制,以及建立 Knowledge Catalog 湖泊來治理資料。

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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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完成「使用 Cloud Run functions 建構無伺服器應用程式」課程,即可獲得入門技能徽章。在這個課程,您將學會如何透過 Google Cloud 控制台和指令列,使用 Cloud Run functions。 技能徽章課程透過實作實驗室和挑戰評量,檢驗學員對於特定產品的實作知識。完成課程或直接進行挑戰實驗室, 即可取得徽章。徽章可證明您的專業能力、提升專業形象,開創更多職涯發展機會。前往個人資料頁面,追蹤您獲得的徽章。

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Recently, a McKinsey report found that Generative AI could add up to $4.4 trillion a year to the global economy, signaling an imminent surge in the demand for GenAI professionals. Now is the perfect time to get a head start and gain hands-on experience with Google Cloud's powerful GenAI tools and techniques, carefully designed to enhance your tech skills and set you on a promising course. Play now to be at the forefront of innovation, shaping the future with GenAI and earning your first Google Cloud GenAI game badge!

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完成使用 Cloud Vision API 分析圖片課程,即可獲得技能徽章。本課程說明如何運用 Cloud Vision API 執行各種工作,包括擷取圖片中的文字。

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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。

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本課程說明如何使用深度學習來建立圖像說明生成模型。您將學習圖像說明生成模型的各個不同組成部分,例如編碼器和解碼器,以及如何訓練和評估模型。在本課程結束時,您將能建立自己的圖像說明生成模型,並使用模型產生圖像說明文字。

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這堂課程將說明變換器架構,以及基於變換器的雙向編碼器表示技術 (BERT) 模型,同時帶您瞭解變換器架構的主要組成 (如自我注意力機制) 和如何用架構建立 BERT 模型。此外,也會介紹 BERT 適用的各種任務,像是文字分類、問題回答和自然語言推論。課程預計約 45 分鐘。

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本課程將介紹注意力機制,說明這項強大技術如何讓類神經網路專注於輸入序列的特定部分。此外,也將解釋注意力的運作方式,以及如何使用注意力來提高各種機器學習任務的成效,包括機器翻譯、文字摘要和回答問題。

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本課程概要說明解碼器與編碼器的架構,這種強大且常見的機器學習架構適用於序列對序列的任務,例如機器翻譯、文字摘要和回答問題。您將認識編碼器與解碼器架構的主要元件,並瞭解如何訓練及提供這些模型。在對應的研究室逐步操作說明中,您將學習如何從頭開始使用 TensorFlow 寫程式,導入簡單的編碼器與解碼器架構來產生詩詞。

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本課程將介紹擴散模型,這是一種機器學習模型,近期在圖像生成領域展現亮眼潛力。概念源自物理學,尤其深受熱力學影響。過去幾年來,在學術界和業界都是炙手可熱的焦點。在 Google Cloud 中,擴散模型是許多先進圖像生成模型和工具的基礎。課程將介紹擴散模型背後的理論,並說明如何在 Vertex AI 上訓練和部署這些模型。

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完成「Introduction to Generative AI」、「Introduction to Large Language Models」和「Introduction to Responsible AI」課程,即可獲得技能徽章。通過最終測驗,就能展現您對生成式 AI 基本概念的掌握程度。 「技能徽章」是 Google Cloud 核發的數位徽章,用於表彰您對 Google Cloud 產品和服務的相關知識。您可以將技能徽章公布在社群媒體的個人資料中,向其他人分享您的成果。

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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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完成「充實中繼資料及發掘 Lakehouse 資料」技能徽章課程,即可證明您具備 BigQuery、 Lakehouse 和 Knowledge Catalog 的相關技能。您會建立 Lakehouse 資料表,並充實中繼資料管理和資料表資料探索功能。

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完成「保護 Lakehouse 資料」技能徽章入門課程,即可證明您具備下列技能:在 Knowledge Catalog 中使用 IAM、BigQuery、 Lakehouse 和 Data Catalog,建立並保護 Lakehouse 資料表。

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完成 在 Google Cloud 實作 Sensitive Data Protection 技能徽章入門課程,證明您具備下列技能:使用 Sensitive Data Protection 服務 (包括 Cloud Data Loss Prevention API) 來檢查、遮蓋及去識別化 Google Cloud 中的機密資料。

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The demand for data skills is growing rapidly, and we want you to get ahead! According to a report by the McKinsey Global Institute, the demand for data scientists and analysts is expected to grow by 150% by 2025. There are a lot of different aspects to any data role, so it's important to start with the basics - and we’ve got you covered. Learn how to tap into ML APIs, dive into your first data lake, and learn how the experts think about securing data. No experience required.

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Welcome to Qwiklabs Trivia for July! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands-on experience on GCP and partner services and earn the July badge.

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Demand for cloud-skilled workers is rising. According to a report by Indeed, cloud computing jobs are expected to grow by 22% over the next five years, much faster than the average for all occupations. Play now to get hands-on experience building with Google Cloud's powerful coding and infrastructure management tools. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential.

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Earn a skill badge by completing the Networking Fundamentals on Google Cloud quest, where you learn how to work with VPC networks and load balancers on Google Cloud. 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, and the final assessment challenge lab, to receive a digital badge that you can share with your network.

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Get started with Go (Golang) by reviewing Go code, and then creating and deploying simple Go apps on Google Cloud. Go is an open source programming language that makes it easy to build fast, reliable, and efficient software at scale. Go runs native on Google Cloud, and is fully supported on Google Kubernetes Engine, Compute Engine, App Engine, Cloud Run, and Cloud Functions. Go is a compiled language and is faster and more efficient than interpreted languages. As a result, Go requires no installed runtime like Node, Python, or JDK to execute.

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完成「Google Cloud Compute 基本操作」任務, 學習如何在 Compute Engine 中使用虛擬機器 (VM)、永久磁碟 和網路伺服器,即可獲得技能徽章。

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完成「在 Google App Engine 上部署及管理應用程式」課程,即可獲得技能徽章。本課程將說明如何搭配 Python、Go 和 PHP 使用 App Engine。

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In this quest, you will learn about Google Cloud’s IoT Core service and its integration with other services like GCS, Dataprep, Stackdriver and Firestore. The labs in this quest use simulator code to mimic IOT devices and the learning here should empower you to implement the same streaming pipeline with real world IoT devices.

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完成 運用 Cloud Run 開發無伺服器應用程式 技能徽章中階課程, 即可證明您具備下列技能:整合 Cloud Run 和 Cloud Storage 以管理資料、 使用 Cloud Run 和 Pub/Sub 架構可復原的非同步系統、 使用 Cloud Run 建構 REST API 閘道,以及在 Cloud Run 建構及部署服務。

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Twelve years ago Lily started the Pet Theory chain of veterinary clinics, and has been expanding rapidly. Now, Pet Theory is experiencing some growing pains: their appointment scheduling system is not able to handle the increased load, customers aren't receiving lab results reliably through email and text, and veteranerians are spending more time with insurance companies than with their patients. Lily wants to build a cloud-based system that scales better than the legacy solution and doesn't require lots of ongoing maintenance. The team has decided to go with serverless technology. For the labs in the Google Cloud Run Serverless Quest, you will read through a fictitious business scenario in each lab and assist the characters in implementing a serverless solution. 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 this quest to receive an exclusive Google…

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This course demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.

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Google Cloud Application Programming Interfaces are the mechanism to interact with Google Cloud Services programmatically. This quest will give you hands-on practice with a variety of GCP APIs, which you will learn through working with Google’s APIs Explorer, a tool that allows you to browse APIs and run their methods interactively. By learning how to transfer data between Cloud Storage buckets, deploy Compute Engine instances, configure Dataproc clusters and much more, Exploring APIs will show you how powerful APIs are and why they are used almost exclusively by proficient GCP users. Enroll in this quest today.

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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 使用 Firebase 開發無伺服器應用程式 技能徽章中階課程, 即可證明您具備下列技能:使用 Firebase 架構及建構無伺服器的網頁應用程式、 運用 Firestore 管理資料庫、使用 Cloud Build 自動部署內容, 以及將 Google 助理功能整合至應用程式。

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Firebase is a backend-as-service (Bass) platform for creating mobile and web applications. In this quest you will learn to build serverless web apps, import data into a serverless database, and build a Google Assistant application with Firebase and its Google Cloud integrations. 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 this quest to receive an exclusive Google Cloud digital badge.

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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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本課程將介紹四種 Google Cloud 網站架構,確保網站具備可用性和擴充性。本課程結束後,請完成本課程結尾的額外挑戰實驗室 「透過 Google Cloud 建構網站」,即可獲得專屬 Google Cloud 數位徽章。 本課程內容取材自影片系列「Get Cooking in Cloud」。

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The hands-on labs in this Quest are structured to give experienced app developers hands-on practice with the state-of-the-art developing applications in Google Cloud. The topics align with the Google Cloud Certified Professional Cloud Developer Certification. These labs follow the sequence of activities needed to create and deploy an app in Google Cloud from beginning to end. Be aware that while practice with these labs will increase your skills and abilities, it is recommended that you also review the exam guide and other available preparation resources.

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In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.

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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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這堂入門課程將說明應用程式開發人員如何運用 Google Cloud 生態系統,建構安全、可擴充的智慧雲端原生應用程式。您將瞭解如何不設定基礎架構就直接開發及擴充應用程式、 執行資料分析、從資料中取得洞察,以及使用預先訓練的機器學習 API 進行開發,即使您不是機器學習專家,也能充分運用技術。您也將體驗各種 Google 服務與 API 之間的完美整合,打造智慧型應用程式。

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In this course you will learn how you to harness serious Google Cloud power and infrastructure. The hands-on labs will give you use cases and you will be tasked with implementing scaling practices utilized by Google’s very own Solutions Architecture team. From developing enterprise grade load balancing and autoscaling, to building continuous delivery pipelines, Google Cloud Solutions I: Scaling your Infrastructure will teach you best practices for taking your Google Cloud projects to the next level.

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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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本課程最適合從事科技或金融職務, 且負責管理 Google Cloud 費用的人士修習。您將學習如何設定帳單帳戶、 整理資源及管理帳單存取權限。 在實作實驗室,您會瞭解如何查看帳單、使用 BigQuery 或 Google 試算表分析帳單資料, 以及使用 Data Studio 建立自訂的帳單資訊主頁。如需影片提及的參考資源連結, 請參閱其他資源文件。

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完成 在 Google Cloud 實作 DevOps 工作流程 技能徽章中階課程, 即可證明您具備下列技能:建立與管理 Git 存放區、 在 Google Kubernetes Engine (GKE) 發布、管理和調度 Deployment, 以及建立 CI/CD 管道,自動建構容器映像檔與執行 GKE 部署作業。

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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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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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透過 DevOps 取得 競爭優勢。DevOps 作業涵蓋組織與文化層面,目標為加速推送軟體、 提高服務穩定性,並為所有軟體相關人員 建立共同擁有權。這堂課程說明如何使用 Google Cloud 提高軟體推送功能的速度、穩定性、可用性和安全性。 開發運作研究與評估計畫已新增至 Google Cloud。想知道自己的團隊表現如何嗎?完成 這個五道選擇題的測驗就能知道答案!

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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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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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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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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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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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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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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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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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在這堂入門課程,您將實際練習使用 Google Cloud 的基礎工具和服務。本課程包含可選擇觀賞的影片, 針對實驗室涵蓋的概念提供更多背景資訊,協助您複習。「Google Cloud 必備知識」 是適合 Google Cloud 學員的第一堂課, 即使您尚未學習或不熟悉雲端知識, 也能從這堂課獲得實務經驗,並應用於第一項 Google Cloud 專案。不管是撰寫 Cloud Shell 指令 和部署第一部虛擬機器,還是在 Kubernetes Engine 或透過負載平衡執行應用程式, 「Google Cloud 必備知識」都是認識平台基本功能的最佳入門資源。

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