加入 登录

Marina Valdés

成为会员时间:2023

钻石联赛

28380 积分
使用 Gemini in BigQuery 提高效率 Earned Apr 3, 2025 EDT
在 BigQuery 中使用 Gemini 模型 Earned Apr 3, 2025 EDT
使用 Dataplex 构建数据网格 Earned Apr 3, 2025 EDT
利用 BigQuery ML 构建预测模型时的数据工程处理 Earned Apr 2, 2025 EDT
在 Google Cloud 上为机器学习 API 准备数据 Earned Apr 1, 2025 EDT
Serverless Data Processing with Dataflow: Foundations Earned Mar 28, 2025 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud Earned Mar 27, 2025 EDT
使用 BigQuery 构建数据仓库 Earned Mar 27, 2025 EDT
Build Streaming Data Pipelines on Google Cloud Earned Mar 26, 2025 EDT
Build Batch Data Pipelines on Google Cloud Earned Mar 25, 2025 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned Mar 20, 2025 EDT
Google Cloud 数据工程简介 Earned Mar 18, 2025 EDT
Preparing for your Professional Data Engineer Journey Earned Nov 4, 2024 EST
Preparing for Your Professional Cloud Network Engineer Journey Earned Jan 29, 2024 EST
Responsible AI: 和 Google Cloud 一起践行 AI 原则 Earned Aug 30, 2023 EDT
Generative AI Fundamentals - 简体中文 Earned Aug 30, 2023 EDT
负责任的 AI 简介 Earned Aug 30, 2023 EDT
大型语言模型简介 Earned Aug 30, 2023 EDT
生成式 AI 简介 Earned Aug 30, 2023 EDT

此课程将探索如何使用 AI 功能套件 Gemini in BigQuery 为“数据到 AI”工作流提供助力。其中涉及到的功能包括数据探索和准备、代码生成和问题排查,以及工作流发现和可视化。此课程包含概念解释、真实使用场景以及实操实验等内容,可帮助数据从业者提升效率并加快流水线开发速度。

了解详情

本课程展示了如何在 BigQuery 中使用 AI/机器学习模型处理生成式 AI 任务。通过一个涉及客户关系管理的实际应用场景,您将学习到使用 Gemini 模型解决业务问题的工作流程。为了便于理解,本课程还将通过使用 SQL 查询和 Python 笔记本的编码解决方案提供分步指导。

了解详情

完成入门技能徽章课程使用 Dataplex 构建数据网格,展示以下方面的技能:使用 Dataplex 构建数据网格, 以在 Google Cloud 上实现数据安全、治理和发现。您将在 Dataplex 中练习和测试自己在标记资产、分配 IAM 角色和评估数据质量方面的技能。

了解详情

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。

了解详情

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 Dataproc 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。

了解详情

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.

了解详情

Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

了解详情

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。

了解详情

In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.

了解详情

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.

了解详情

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.

了解详情

在本课程中,您将了解 Google Cloud 数据工程、数据工程师的角色和职责,以及相关的 Google Cloud 产品和服务。您还将了解如何应对数据工程挑战。

了解详情

This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

了解详情

This course helps you structure your preparation for the Professional Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.

了解详情

随着企业对人工智能和机器学习的应用越来越广泛,以负责任的方式构建这些技术也变得更加重要。但对很多企业而言,真正践行 Responsible AI 并非易事。如果您有意了解如何在组织内践行 Responsible AI,本课程正适合您。 本课程将介绍 Google Cloud 目前如何践行 Responsible AI,以及从中总结的最佳实践和经验教训,便于您以此为框架构建自己的 Responsible AI 方法。

了解详情

完成 Introduction to Generative AI、Introduction to Large Language Models 和 Introduction to Responsible AI 三门课程,赢取技能徽章。通过最终测验,即表明您理解了生成式 AI 的基本概念。 技能徽章是由 Google Cloud 颁发的数字徽章,旨在认可您对 Google Cloud 产品与服务的了解程度。公开您的个人资料并将技能徽章添加到您的社交媒体个人资料中,以此来分享您获得的成就。

了解详情

这是一节入门级微课程,旨在解释什么是负责任的 AI、它的重要性,以及 Google 如何在自己的产品中实现负责任的 AI。此外,本课程还介绍了 Google 的 7 个 AI 开发原则。

了解详情

这是一节入门级微学习课程,探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能,还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。

了解详情

这是一节入门级微课程,旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。

了解详情