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Khoa Trần

Member since 2021

Silver League

9300 points
Analyzing and Visualizing Data in Looker Earned Sep 28, 2022 EDT
Build a Certification Study Guide: PDE Exam Prep Earned Sep 28, 2022 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned Sep 27, 2022 EDT
Looker 資料模型管理 Earned Sep 27, 2022 EDT
Google Kubernetes Engine Best Practices: Security Earned Sep 27, 2022 EDT
[DEPRECATED] Secure Workloads in Google Kubernetes Engine Earned Sep 27, 2022 EDT
從 BigQuery 資料取得深入分析結果 Earned Sep 27, 2022 EDT
Machine Learning in the Enterprise Earned Sep 19, 2022 EDT
在 Google Cloud 為機器學習 API 準備資料 Earned Nov 23, 2021 EST
運用 Cloud Run 開發無伺服器應用程式 Earned Nov 22, 2021 EST
使用 BigQuery ML 為預測模型進行資料工程 Earned Nov 22, 2021 EST
為 Looker 資訊主頁和報表準備資料 Earned Nov 22, 2021 EST
使用資料庫遷移服務將 MySQL 資料遷移至 Cloud SQL Earned Nov 22, 2021 EST
Migrating MySQL data to Cloud SQL using Database Migration Service Earned Nov 22, 2021 EST
DEPRECATED BigQuery for Data Warehousing Earned Nov 22, 2021 EST
瞭解 Looker 中的 LookML Earned Nov 22, 2021 EST
Scientific Data Processing Earned Nov 21, 2021 EST
在 Looker 應用進階 LookML 概念 Earned Nov 21, 2021 EST
DEPRECATED BigQuery Basics for Data Analysts Earned Nov 20, 2021 EST
使用 BigQuery 進行機器學習 Earned Nov 20, 2021 EST
運用 BigQuery ML 建立機器學習模型 Earned Nov 20, 2021 EST
透過 BigQuery 建構資料倉儲 Earned Nov 18, 2021 EST
DEPRECATED Explore Machine Learning Models with Explainable AI Earned Nov 11, 2021 EST

In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam. You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.

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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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完成 Looker 資料模型管理技能徽章中階課程,即可證明您具備下列技能:維護 LookML 專案的健全性、運用 SQL Runner 驗證資料、採用 LookML 最佳做法、改良查詢及 報表,並執行永久衍生資料表和快取政策。

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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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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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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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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.

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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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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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完成「為 Looker 資訊主頁和報表準備資料」技能徽章入門課程, 即可證明您具備下列技能:可篩選、排序和 pivot 資料、合併不同的 Looker 探索結果, 還能使用函式和運算子建構 Looker 資訊主頁和報表,取得資料分析結果和圖表。

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完成 使用資料庫遷移服務將 MySQL 資料遷移至 Cloud SQL 技能徽章入門課程,證明您具備下列技能: 使用「資料庫遷移服務」中各種可用的工作類型和連線選項, 將 MySQL 資料遷移至 Cloud SQL,以及在執行「資料庫遷移服務」工作時 遷移 MySQL 使用者資料。

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This course offers hands-on practice with migrating MySQL data to Cloud SQL using Database Migration Service. You start with an introductory lab that briefly reviews how to get started with Cloud SQL for MySQL, including how to connect to Cloud SQL instances using the Cloud Console. Then, you continue with two labs focused on migrating MySQL databases to Cloud SQL using different job types and connectivity options available in Database Migration Service. The course ends with a lab on migrating MySQL user data when running Database Migration Service jobs.

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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. 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. 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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在本課程中,您將實際操作 Looker 的 LookML。您將學習如何編寫 LookML 程式碼,建立新的維度和測量指標、建立衍生資料表並彙整至探索、篩選探索,以及在 LookML 中定義快取政策。

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Big data, machine learning, and scientific data? It sounds like the perfect match. In this course, you will get hands-on practice with GCP services like BigQuery, Managed Service for Apache Spark, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.

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在本課程中,您將透過實際操作,瞭解如何在 Looker 應用進階 LookerML 概念。您將學習如何使用 Liquid 自訂和建立動態維度 和測量指標、建構動態 SQL 衍生資料表和自訂的原生衍生資料表, 並運用擴充參數將 LookML 程式碼模組化。

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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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不想花費大把時間,想在幾分鐘內只靠 SQL,就建立好機器學習模型嗎?透過 BigQuery ML,資料分析師可以運用現有的 SQL 工具和技巧,建立、訓練、評估模型, 並使用模型進行預測,降低機器學習的使用門檻。在 本系列的實驗室,您會測試不同類型的模型,瞭解 優良模型應具備的條件。

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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 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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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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