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Guilherme Cezar

成为会员时间:2022

云端数据转换 Earned Dec 11, 2025 EST
云端数据管理和存储 Earned Dec 11, 2025 EST
讲故事的力量:如何在云端可视化数据 Earned Dec 11, 2025 EST
融会贯通:为云数据分析师岗位做好准备 Earned Dec 11, 2025 EST
Google Cloud 数据分析功能简介 Earned Dec 11, 2025 EST
Introduction to Data Analytics in Google Cloud Earned Nov 29, 2024 EST
Put It All Together: Prepare for a Cloud Data Analyst Job Earned Nov 29, 2024 EST
The Power of Storytelling: How to Visualize Data in the Cloud Earned Nov 28, 2024 EST
Data Management and Storage in the Cloud Earned Nov 27, 2024 EST
Data Transformation in the Cloud Earned Nov 27, 2024 EST
构建安全的 Google Cloud 网络 Earned May 10, 2023 EDT
Google Cloud Fundamentals for AWS Professionals Earned Jun 7, 2022 EDT
通过 BigQuery ML 创建机器学习模型 Earned Jun 3, 2022 EDT
在 Google Cloud 上为机器学习 API 准备数据 Earned May 31, 2022 EDT
Google Cloud 基础知识:核心基础设施 Earned May 31, 2022 EDT
在 Google Cloud 上设置应用开发环境 Earned May 27, 2022 EDT
为 Compute Engine 实现云负载均衡 Earned May 26, 2022 EDT
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales Earned May 26, 2022 EDT

本课程是 Google Cloud 数据分析认证计划的第三门课程(共五门)。在本课程中,您将首先了解从收集数据到获取数据分析洞见的整个数据历程。然后,您将学习如何使用 SQL 将原始数据转换为可用格式。接下来,您将学习如何使用数据流水线转换大量数据。最后,您会获得相关经验,熟悉如何将数据转换策略应用于真实数据集以满足业务需求。

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本课程是 Google Cloud 数据分析认证计划的第二门课程(共五门)。在本课程中,您将探索数据的结构形式和组织方式。您将获得数据湖仓一体架构和云组件(如 BigQuery、Google Cloud Storage 和 DataProc)的实操经验,以便高效地存储、分析和处理大型数据集。

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本课程是 Google Cloud 数据分析认证计划的第四门课程(共五门课程)。在本课程中,您将重点学习在云端可视化数据的相关技能,其中数据可视化可分为五个关键阶段:讲故事、规划、探索数据、构建可视化图表以及与他人共享数据。您还将获得实操经验,尝试使用 UI(界面)/UX(用户体验)技能来制作线框图,从而设计出有影响力的云原生可视化图表,并使用云原生数据可视化工具来探索数据集、创建报告和构建信息中心,从而推动决策并促进协作。

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本课程是 Google Cloud 数据分析认证计划的第五门课程(共五门)。在本课程中,你将综合运用前 4 门课程所学的基础知识和技能,实操完成一个结业项目,全面探索整个数据生命周期。您将练习使用云端工具来有效地获取、存储、处理、分析、直观呈现数据并传达数据分析洞见。课程结束时,您将完成一个项目,证明您在以下方面的熟练程度:高效地设计数据结构以整理来自多个来源的数据、向不同利益相关方展示解决方案,以及使用云端软件直观呈现数据分析洞见。您还将更新个人简历并练习面试技巧,为求职申请与面试环节做好准备。

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本课程是 Google Cloud 数据分析认证的第一门课程(共五门)。在本课程中,您将认识云数据分析领域,并了解云数据分析师在数据获取、存储、处理和可视化方面的角色和职责。您将探索 BigQuery 和 Cloud Storage 等基于 Google Cloud 的工具的架构,以及如何使用这些工具有效地设计数据结构,以及展示和报告数据。

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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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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 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 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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完成构建安全的 Google Cloud 网络课程,赢取技能徽章。在此课程中,您将了解与网络有关的众多 资源,以便在 Google Cloud 上构建、扩缩和保护自己的应用。

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Google Cloud Fundamentals for AWS Professionals introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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完成中级技能徽章课程通过 BigQuery ML 创建机器学习模型,展示您在以下方面的技能: 使用 BigQuery ML 创建和评估机器学习模型,以执行数据预测。

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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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“Google Cloud 基础知识:核心基础设施”介绍在使用 Google Cloud 时会遇到的重要概念和术语。本课程通过视频和实操实验来介绍并比较 Google Cloud 的多种计算和存储服务,并提供重要的资源和政策管理工具。

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完成“在 Google Cloud 上设置应用开发环境”课程,赢取技能徽章;通过该课程,您将了解如何使用以下技术的基本功能来构建和连接以存储为中心的云基础设施: Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。

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完成入门级技能徽章课程为 Compute Engine 实现云负载均衡,展示以下方面的技能: 在 Compute Engine 中创建和部署虚拟机 以及配置网络和应用负载均衡器。

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This course, Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Cloud Computing Fundamentals .The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud …

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