Earn a skill badge by completing the Build Custom Processors with Document AI course. You learn how to extract data and classify documents by creating custom ML models specific to your business needs. This course teaches the foundation skills of building your own processors, working with optical character recognition, form parsing, processor creation, and uptraining the DocumentAI model.
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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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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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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。
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完成 在 Agent Platform 中设计提示入门技能徽章课程，展示以下方面的技能： Agent Platform 中的提示工程、图片分析和多模态生成式技术。探索如何编写有效的提示，指导生成式 AI 输出， 以及将 Gemini 模型应用于真实的营销场景。
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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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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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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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Build Custom Processors with Document AI [Deprecated]
Earned Mar 7, 2025 EST
Build Batch Data Pipelines on Google Cloud
Earned Mar 6, 2025 EST
在 Google Cloud 上为机器学习 API 准备数据
Earned Mar 1, 2025 EST
Google Cloud 数据工程简介
Earned Jan 31, 2025 EST
在 Agent Platform 中设计提示
Earned Jan 31, 2025 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned Sep 5, 2024 EDT
探索生成式 AI - Agent Platform
Earned Aug 24, 2024 EDT
Build a Certification Study Guide: PDE Exam Prep
Earned Aug 6, 2024 EDT