Vertex AI is now Gemini Enterprise Agent Platform! We are currently updating our content to reflect this change. Please bear with us if you encounter naming inconsistencies during this transition.
在 Google Cloud 控制台中运用您的技能
Nick Nöthling
成为会员时间：2025
Google DeepMind: Train A Small Language Model
Earned Mar 13, 2026 EDT
通过 BigQuery ML 创建机器学习模型
Earned Feb 24, 2026 EST
Build Streaming Data Pipelines on Google Cloud
Earned Feb 24, 2026 EST
Build Batch Data Pipelines on Google Cloud
Earned Feb 20, 2026 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned Feb 19, 2026 EST
Google Cloud 数据工程简介
Earned Feb 19, 2026 EST
Preparing for your Professional Data Engineer Journey
Earned Jan 29, 2026 EST
使用 BigQuery 机器学习推理功能
Earned Jan 26, 2026 EST
面向数据科学家和分析师的 Gemini
Earned Jan 26, 2026 EST
AI Boost Bites: Automate tasks with Gemini and Apps Script
Earned Jul 29, 2025 EDT
利用 Vertex AI 实现机器学习运维 (MLOps)：模型评估
Earned Jul 15, 2025 EDT
适用于生成式 AI 的机器学习运维 (MLOps)
Earned Jul 15, 2025 EDT
Complete the advanced Google DeepMind: Train A Small Language Model skill badge by completing this course to demonstrate skills in the following: formulating real-world language model research problems; building a simple tokenizer; preparing a dataset for training a transformer language model; running the training loop of a small language model. Access this lab at no-cost by signing up for the no-cost subscription. Receive 35 free credits each month!
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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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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.
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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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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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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.
在本课程中，您将了解 Gemini（Google Cloud 的生成式 AI 赋能的协作工具）如何帮助分析客户数据并预测产品销售情况。此外，您还将了解如何在 BigQuery 中使用客户数据来识别、开发新客户并对其进行分类。通过动手实验，您将体验 Gemini 如何改进数据分析和机器学习工作流。
Duet AI 已更名为 Gemini，这是我们的新一代模型。
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This video covers how to use Gemini and Apps Script to automate manual tasks across Google Workspace. You'll learn to prompt Gemini to generate Apps Script code that automatically drafts email reminders in Google Sheets for tasks not marked 'Complete.' Automate your workflow with little to no technical expertise, freeing up time for more important work and eliminating manual follow-ups.
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本课程介绍了 Responsible AI 的概念和 AI 原则，还介绍了在 AI/机器学习实践中识别公平性与偏见以及减少偏见的实用技巧，同时探索了使用 Google Cloud 产品和开源工具来实施 Responsible AI 最佳实践的实用方法和工具。
本课程能让机器学习从业者掌握评估生成式和预测式 AI 模型的基本工具、方法和最佳实践。要确保机器学习系统在实际运用中提供可靠、准确、高效的结果，做好模型评估至关重要。
学员将深入了解各项评估指标、方法及如何在不同模型类型和任务中适当应用这些指标和方法。课程将着重介绍生成式 AI 模型带来的独特挑战，并提供有效解决这些挑战的策略。通过利用 Google Cloud 的 Vertex AI Platform，学员可学习如何在模型选择、优化和持续监控工作中实施卓有成效的评估流程。
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本课程致力于为您提供所需的知识和工具，让您能够了解 MLOps 团队在部署和管理生成式 AI 模型以及探索 Vertex AI 如何帮助 AI 团队简化 MLOps 流程时面临的独特挑战，并帮助您在生成式 AI 项目中取得成功。
Google DeepMind: Train A Small Language Model
Earned Mar 13, 2026 EDT
通过 BigQuery ML 创建机器学习模型
Earned Feb 24, 2026 EST
Build Streaming Data Pipelines on Google Cloud
Earned Feb 24, 2026 EST
Build Batch Data Pipelines on Google Cloud
Earned Feb 20, 2026 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned Feb 19, 2026 EST
Google Cloud 数据工程简介
Earned Feb 19, 2026 EST
Preparing for your Professional Data Engineer Journey
Earned Jan 29, 2026 EST
使用 BigQuery 机器学习推理功能
Earned Jan 26, 2026 EST
面向数据科学家和分析师的 Gemini
Earned Jan 26, 2026 EST
AI Boost Bites: Automate tasks with Gemini and Apps Script
Earned Jul 29, 2025 EDT
面向开发者的 Responsible AI：公平性与偏见
Earned Jul 29, 2025 EDT
创建图片标注模型
Earned Jul 29, 2025 EDT
Transformer 模型和 BERT 模型
Earned Jul 29, 2025 EDT
编码器-解码器架构
Earned Jul 29, 2025 EDT
注意力机制
Earned Jul 29, 2025 EDT
使用 Gemini in BigQuery 提高效率
Earned Jul 29, 2025 EDT
在 BigQuery 中使用 Gemini 模型
Earned Jul 29, 2025 EDT
使用 BigQuery 实现多模态向量搜索
Earned Jul 29, 2025 EDT
使用 BigQuery 创建嵌入、向量搜索和 RAG
Earned Jul 29, 2025 EDT
图像生成简介
Earned Jul 28, 2025 EDT
矢量搜索和嵌入
Earned Jul 28, 2025 EDT
提升 Gemini 模型的能力
Earned Jul 18, 2025 EDT
使用多模态 Gemini 和多模态 RAG 检查富文档
Earned Jul 17, 2025 EDT
利用 Vertex AI 实现机器学习运维 (MLOps)：模型评估
Earned Jul 15, 2025 EDT
适用于生成式 AI 的机器学习运维 (MLOps)
Earned Jul 15, 2025 EDT