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Quốc Hồ Bảo

成为会员时间：2021

钻石联赛

22605 积分
Serverless Data Processing with Dataflow: Foundations Earned Sep 8, 2024 EDT
BigQuery 流式数据分析 Earned Sep 2, 2024 EDT
使用 BigQuery 构建数据仓库 Earned Sep 2, 2024 EDT
从 BigQuery 数据中挖掘数据洞见 Earned Sep 1, 2024 EDT
在 Google Cloud 上为机器学习 API 准备数据 Earned Sep 1, 2024 EDT
利用 BigQuery ML 构建预测模型时的数据工程处理 Earned Aug 18, 2024 EDT
在 Google Cloud 中管理 Kubernetes Earned Apr 20, 2024 EDT
探索生成式 AI - Agent Platform Earned Mar 23, 2024 EDT
Build Batch Data Pipelines on Google Cloud Earned Mar 18, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned Feb 9, 2024 EST
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned Feb 7, 2024 EST
Build a Certification Study Guide: PDE Exam Prep Earned Feb 5, 2024 EST

This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.

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完成 BigQuery 流式数据分析技能徽章课程，赢取技能徽章 。在这门课程中，您将结合使用 Pub/Sub、Dataflow 和 BigQuery 来实现流式 数据分析。

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完成中级技能徽章课程使用 BigQuery 构建数据仓库，展示以下技能： 联接数据以创建新表、排查联接故障、使用并集附加数据、创建日期分区表， 以及在 BigQuery 中使用 JSON、数组和结构体。

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完成入门级技能徽章课程“从 BigQuery 数据中挖掘数据洞见”，展示您在以下方面的技能： 编写 SQL 查询、查询公共表、将示例数据加载到 BigQuery 中、 在 BigQuery 中使用查询验证器排查常见的语法错误，以及通过连接到 BigQuery 数据在 Data Studio 中 创建报告。

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完成入门级技能徽章课程在 Google Cloud 上为机器学习 API 准备数据，展示以下技能： 使用 Dataprep by Trifacta 清理数据、在 Dataflow 中运行数据流水线、在 Managed Service for Apache Spark 中创建集群和运行 Apache Spark 作业，以及调用机器学习 API，包括 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。

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完成中级技能徽章课程利用 BigQuery ML 构建预测模型时的数据工程处理， 展示自己在以下方面的技能：利用 Dataprep by Trifacta 构建 BigQuery 数据转换流水线； 利用 Cloud Storage、Dataflow 和 BigQuery 构建提取、转换和加载 (ETL) 工作流； 以及利用 BigQuery ML 构建机器学习模型。

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完成在 Google Cloud 中管理 Kubernetes这一中级技能徽章课程， 展示您在以下方面的技能：使用 kubectl 管理部署、监控并 调试在 Google Kubernetes Engine (GKE) 上运行的应用，以及持续交付技术。

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探索生成式 AI - Agent Platform”课程包含一系列实验， 指导用户在 Google Cloud 平台上使用生成式 AI。通过这些实验，您将了解 如何在 Agent Platform 中使用 Gemini 模型。您还将了解提示设计、最佳实践， 以及如何使用生成式 AI 进行构思、文本分类、文本提取、文本摘要等。此外， 您将学习如何通过 Agent Platform 中的自定义训练来训练基础模型， 从而对其进行调优，以及如何将其部署到 Agent Platform 中的端点。

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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting. Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.

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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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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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