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Bill Chang

Member since 2021

Silver League

7200 points
DEPRECATED Explore Machine Learning Models with Explainable AI Earned Jun 21, 2021 EDT
運用 BigQuery ML 建立機器學習模型 Earned Jun 21, 2021 EDT
從 BigQuery 資料取得深入分析結果 Earned Jun 21, 2021 EDT
DEPRECATED Application Development - Python Earned Jun 18, 2021 EDT
運用 Cloud Run 開發無伺服器應用程式 Earned Jun 18, 2021 EDT
在 Google Cloud 使用機器學習 API Earned Jun 18, 2021 EDT
透過 Google Cloud 建構網站 Earned Jun 17, 2021 EDT
Flutter Development Earned Jun 17, 2021 EDT
Build Apps & Websites with Firebase Earned Jun 16, 2021 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant Earned Jun 16, 2021 EDT
[DEPRECATED] Build Interactive Apps with Google Assistant Earned Jun 16, 2021 EDT
在 Google Cloud 為機器學習 API 準備資料 Earned Jun 15, 2021 EDT
機器學習簡介：語言處理 Earned Jun 15, 2021 EDT
使用 Firebase 開發無伺服器應用程式 Earned Jun 11, 2021 EDT
在 Compute Engine 導入 Cloud Load Balancing Earned Jun 8, 2021 EDT
Google Cloud 必備知識 Earned Jun 8, 2021 EDT

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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完成「運用 BigQuery ML 建立機器學習模型」技能徽章中階課程，即可證明您具備下列技能： 可使用 BigQuery ML 建立及評估機器學習模型，並根據資料進行預測。

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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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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.

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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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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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Explore the fundamentals of Flutter application development in this hands-on quest! Within this quest, you will build a "Hello World" Flutter application, design a frontend for a shopping application, and learn how to connect your Flutter applications to backend services. Each lab in this quest utilizes a pre-provisioned development environment allowing minimal setup to get into the application code!

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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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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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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 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 Managed Service for Apache Spark 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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大家都知道，機器學習是發展最快的科技領域之一， 而 Google Cloud Platform 在這方面功不可沒。 GCP 提供多種 API，凡是與機器學習相關的任務，幾乎都能處理。您將在本入門課程的 實驗室，實際演練機器學習技術 在語言處理方面的應用，學會如何從文中擷取實體資訊、 執行情緒和語法分析，並使用 Speech-to-Text API 轉錄語音。

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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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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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