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Bruno Silva Saba

成为会员时间：2021

青铜联赛

3210 积分
Analyzing and Visualizing Data in Looker - Locales Earned Jan 4, 2023 EST
在 Compute Engine 導入 Cloud Load Balancing Earned May 17, 2022 EDT
使用 BigQuery ML 為預測模型進行資料工程 Earned May 13, 2022 EDT
在 Google Cloud 設定應用程式開發環境 Earned Apr 27, 2022 EDT
基本概念：基礎架構 Earned Apr 27, 2022 EDT
BigQuery for Data Analysis I Earned Feb 23, 2022 EST
在 Google Cloud 為機器學習 API 準備資料 Earned Nov 12, 2021 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned Oct 29, 2021 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned Oct 8, 2021 EDT

This course, Analyzing and Visualizing Data in Looker - Locales, is intended for non-English learners only. If you wish to take this content in English, please enroll in Analyzing and Visualizing Data in Looker. This course enables you to upscale your data warehouse solutions with an introduction to Looker for data exploration, analysis, and visualization. Upon completing this course, you will be able to start exploring your organization’s Looker instance and analyzing the available data to create shareable visualizations and reports.

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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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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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Welcome Gamers! Learn BigQuery and Cloud SQL, all while having fun! You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game 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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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.

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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.

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