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Dustin McClure

Member since 2021

Diamond League

30480 points
Google Cloud 資料分析功能簡介 Earned Dec 10, 2025 EST
在 Cloud 管理與儲存資料 Earned Dec 10, 2025 EST
在 Cloud 轉換資料 Earned Dec 9, 2025 EST
資料敘事的強大力量:如何在 Cloud 以圖表呈現資料 Earned Dec 9, 2025 EST
綜合應用:為 Cloud 資料分析師工作做準備 Earned Dec 9, 2025 EST
機器學習簡介:語言處理 Earned Jun 7, 2025 EDT
運用 BigQuery ML 建立機器學習模型 Earned Jun 5, 2025 EDT
在 Google Cloud 為機器學習 API 準備資料 Earned Jun 1, 2025 EDT
NCAA® March Madness®: Bracketology with Google Cloud Earned Apr 27, 2025 EDT
Build a Certification Study Guide: PMLE Earned Apr 20, 2025 EDT
Put It All Together: Prepare for a Cloud Data Analyst Job Earned Mar 22, 2025 EDT
The Power of Storytelling: How to Visualize Data in the Cloud Earned Mar 20, 2025 EDT
Data Transformation in the Cloud Earned Mar 17, 2025 EDT
Data Management and Storage in the Cloud Earned Mar 15, 2025 EDT
Introduction to Data Analytics in Google Cloud Earned Feb 7, 2025 EST
在 Compute Engine 導入 Cloud Load Balancing Earned Dec 2, 2024 EST
Google Cloud 基礎知識:核心基礎架構 Earned Nov 18, 2024 EST
Google Cloud 必備知識 Earned Jan 16, 2023 EST

這是 Google Cloud 資料分析專業證書五堂課程中的第一堂。在本課程中,您將瞭解雲端資料分析領域的定義,並說明雲端資料分析師在資料擷取、儲存、處理和視覺化方面的角色與職責。您將瞭解 BigQuery 和 Cloud Storage 等 Google Cloud 工具的架構,以及如何運用這些工具有效組織、呈現及彙整資料。

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這是 Google Cloud 資料分析專業證書五堂課程中的第二堂。本課程將帶您瞭解資料的結構化和組織方式。您將透過實作,瞭解資料湖倉架構和 BigQuery、Google Cloud Storage 與 DataProc 等雲端元件,有效率地儲存、分析及處理大型資料集。

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Google Cloud 資料分析專業證書課程共有五堂課程,這是第三堂。本課程會先簡要說明資料歷程,從最初的資料收集,一直到最後的洞察分析。接著,您將依序學習如何使用 SQL 將原始資料轉換為可用的格式、怎麼透過資料管道轉換大量資料。最後,您將練習如何將轉換策略應用於實際資料集,滿足業務需求。

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這是 Google Cloud Data Analytics 專業證書五堂課程中的第四堂。本課程著重於培養雲端資料圖表製作的技能,共分五個主要階段:敘事、規劃、探索資料、建立圖表,以及與他人分享資料。您還會實際使用 UI/UX 技能,繪製具說服力的雲端原生圖表線框稿,並運用雲端原生資料圖表工具探索資料集、建立報表和資訊主頁,推動決策並促進協作。

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這是 Google Cloud Data Analytics 專業證書五堂課程中的第五堂。在本課程中,您將結合第一到第四堂課程的基礎知識和技能,並活用所學,透過專題實作呈現完整的資料生命週期。您將練習使用雲端式工具,有效率地取得、儲存、處理、分析資料,並以圖表呈現及傳達資料洞察結果。本課程結束後,您將完成一項專案,證明自己精通於有效整理多個來源的資料、向不同相關人士說明解決方案,以及運用雲端式軟體將資料洞察結果以圖表呈現。此外,您還會更新履歷,並練習面試技巧,為應徵和面試做好準備。

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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「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 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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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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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.

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This is the fifth of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll combine and apply the foundational knowledge and skills from courses 1-4 in a hands-on Capstone project that focuses on the full data lifecycle project. You’ll practice using cloud-based tools to acquire, store, process, analyze, visualize, and communicate data insights effectively. By the end of the course, you’ll have completed a project demonstrating their proficiency in effectively structuring data from multiple sources, presenting solutions to varied stakeholders, and visualizing data insights using cloud-based software. You’ll also update your resume and practice interview techniques to help prepare for applying and interviewing for jobs.

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This is the fourth of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll focus on developing skills in the five key stages of visualizing data in the cloud: storytelling, planning, exploring data, building visualizations, and sharing data with others. You’ll also gain experience using UI/UX skills to wireframe impactful, cloud-native visualizations and work with cloud-native data visualization tools to explore datasets, create reports, and build dashboards that drive decisions and foster collaboration.

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This is the third of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll begin by getting an overview of the data journey, from collection to insights. You’ll then learn how to use SQL to transform raw data into a usable format. Next, you’ll learn how to transform high volumes of data with a data pipeline. Finally, you’ll gain experience applying transformation strategies to real data sets to solve business needs.

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This is the second of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll explore how data is structured and organized. You’ll gain hands-on experience with the data lakehouse architecture and cloud components like BigQuery, Google Cloud Storage, and DataProc to efficiently store, analyze, and process large datasets.

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This is the first of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll define the field of cloud data analysis and describe roles and responsibilities of a cloud data analyst as they relate to data acquisition, storage, processing, and visualization. You’ll explore the architecture of Google Cloud-based tools, like BigQuery and Cloud Storage, and how they are used to effectively structure, present, and report data.

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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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「Google Cloud 基礎知識:核心基礎架構」介紹了在使用 Google Cloud 時會遇到的重要概念和術語。本課程會透過影片和實作實驗室,介紹並比較 Google Cloud 的多種運算和儲存服務,同時提供重要的資源和政策管理工具。

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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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