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Omar Irfan Khan

成为会员时间：2021

黄金联赛

21305 积分
注意力机制 Earned Feb 1, 2025 EST
图像生成简介 Earned Feb 1, 2025 EST
Responsible AI: 和 Google Cloud 一起践行 AI 原则 Earned Feb 1, 2025 EST
适用于安全工程师的 Gemini Earned Jan 31, 2025 EST
适用于端到端 SDLC 的 Gemini Earned Jan 31, 2025 EST
适用于生成式 AI 的机器学习运维 (MLOps) Earned Jan 30, 2025 EST
Google Vids 中的 Gemini Earned Jan 30, 2025 EST
Google 云端硬盘中的 Gemini Earned Jan 30, 2025 EST
Google Meet 中的 Gemini Earned Jan 30, 2025 EST
Google 表格中的 Gemini Earned Jan 30, 2025 EST
Google 幻灯片中的 Gemini Earned Jan 30, 2025 EST
Google 文档中的 Gemini Earned Jan 30, 2025 EST
Gmail 中的 Gemini Earned Jan 30, 2025 EST
内置 Gemini 的 Google Workspace：AI 工作流基础知识 Earned Jan 30, 2025 EST
Serverless Data Processing with Dataflow: Develop Pipelines Earned Jan 30, 2025 EST
How Google Does Machine Learning Earned Oct 31, 2021 EDT
Build a Certification Study Guide: PDE Exam Prep Earned Oct 25, 2021 EDT
Serverless Data Processing with Dataflow: Foundations Earned Oct 21, 2021 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud Earned Oct 20, 2021 EDT
Build Streaming Data Pipelines on Google Cloud Earned Oct 19, 2021 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned Oct 18, 2021 EDT
利用 BigQuery ML 构建预测模型时的数据工程处理 Earned Oct 14, 2021 EDT
API Development with the Apigee API Platform Earned Oct 12, 2021 EDT
API Security with the Apigee API Platform Earned Oct 12, 2021 EDT
API Design and Fundamentals with the Apigee API Platform Earned Oct 12, 2021 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned Oct 12, 2021 EDT
在 Google Cloud 上设置应用开发环境 Earned Oct 11, 2021 EDT
为 Compute Engine 实现云负载均衡 Earned Oct 8, 2021 EDT
Google Cloud 基础知识 Earned Oct 8, 2021 EDT

本课程将向您介绍注意力机制，这是一种强大的技术，可令神经网络专注于输入序列的特定部分。您将了解注意力的工作原理，以及如何使用它来提高各种机器学习任务的性能，包括机器翻译、文本摘要和问题解答。

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本课程向您介绍扩散模型。这类机器学习模型最近在图像生成领域展现出了巨大潜力。扩散模型的灵感来源于物理学，特别是热力学。过去几年内，扩散模型成为热门研究主题并在整个行业开始流行。Google Cloud 上许多先进的图像生成模型和工具都是以扩散模型为基础构建的。本课程向您介绍扩散模型背后的理论，以及如何在 Vertex AI 上训练和部署此类模型。

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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。

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在本课程中，您将了解 Gemini（Google Cloud 推出的一款依托生成式 AI 的协作工具）如何帮助您保护您的云环境和资源。您将学习如何将示例工作负载部署到 Google Cloud 环境中，以及如何借助 Gemini 识别和修复安全配置错误。您可以通过实操实验了解如何利用 Gemini 来改善云安全状况。 Duet AI 已更名为 Gemini，这是我们的新一代模型。

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在本课程中，您将了解 Gemini（Google Cloud 推出的一款依托生成式 AI 的协作工具）如何帮助您使用 Google 产品和服务开发、测试、部署和管理应用。在 Gemini 的协助下，您可以学习如何开发和构建 Web 应用、修复应用中的错误、开发测试和查询数据。您可以通过实操实验了解如何利用 Gemini 来改进软件开发生命周期 (SDLC)。 Duet AI 已更名为 Gemini，这是我们的新一代模型。

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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。

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本课程将介绍 Google Vids，这是 Google Workspace 中一款由 AI 赋能的创作工具，可帮助您将原始文档转换为专业、引人入胜的视频，无需任何编辑经验。您将学习如何使用模板和自动化工具快速生成草稿，以及如何通过基于转写稿的编辑、动态视觉增强和自定义音乐来定制内容。最后，您将探索如何集成 AI 虚拟形象和旁白，在各种业务场景中无缝讲解演示文稿。

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本课程介绍如何在 Google 云端硬盘中使用 Gemini 来管理和检索文件。了解如何使用自然语言定位资源、在无需打开文件的情况下通过 AI 概览直接提取特定事实、即时总结多种媒体格式的内容，并将文件集合保存为“项目”以进行可重复的研究。

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本课程介绍如何使用 Google Meet 中的 Gemini 来提升视频协作体验。了解如何自动生成会议记录、利用实时文本和语音翻译功能、在不打扰他人的情况下快速了解错过的讨论，以及即时优化音视频质量。

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本课程介绍如何使用 Google 表格中的 Gemini 自动整理数据和处理复杂数字。了解如何根据原始文本构建表格、使用自然语言自动填充数据、按需生成原生电子表格公式，以及快速提取高级分析洞见或可视化图表，而无需具备高级电子表格专业知识。

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本课程将介绍如何利用 Google 幻灯片中的 Gemini 将构思转化为极具视觉冲击力的演示文稿。学习如何通过单个提示词或现有源文档生成结构化幻灯片组，利用自动设计增强功能优化布局，创建自定义矢量图和照片，并动态撰写幻灯片正文及精准的演讲者备注。

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本课程介绍如何使用 Google 文档中的 Gemini 来简化写作和内容创作。了解如何从头开始起草文档，使用互动式工具优化写作语气和清晰度，总结复杂文件，以及将长篇文本无缝转换为适用于其他 Google Workspace 应用的结构化资产。

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本课程介绍如何使用 Gmail 中的 Gemini 来优化邮件管理。了解如何总结冗长的会话串、使用自然语言检索信息、起草专业回复，以及直接在收件箱中整理沟通策略。

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Gemini for Google Workspace 可在 Google Workspace 中为客户提供生成式 AI 功能。在本学习路线中，您将了解 Gemini 的主要功能，以及如何在 Google Workspace 中使用它们来提高工作效率。

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In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.

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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.

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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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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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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.

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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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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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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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In this course, you learn how to create APIs that utilize multiple services and how you can use custom code on Apigee. You will also learn about fault handling, and how to share logic between proxies. You learn about traffic management and caching. You also create a developer portal, and publish your API to the portal. You learn about logging and analytics, as well as CI/CD and the different deployment models supported by Apigee. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform. This is the third and final course of the Developing APIs with the Apigee API Platform course series.

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In this course, you learn how to secure your APIs. You explore the security concerns you will encounter for your APIs. You learn about OAuth, the primary authorization method for REST APIs. You will learn about JSON Web Tokens (JWTs) and federated security. You also learn about securing against malicious requests, safely sending requests across a public network, and how to secure your data for users of Apigee. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform. This is the second course of the Developing APIs with the Apigee API Platform series. After completing this course, enroll in the API Development with the Apigee API Platform course.

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In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API lifecycle, and how the Apigee API platform helps you manage all aspects of the lifecycle. You learn how APIs can be designed using API proxies, and how APIs are packaged as API products to be used by app developers. Through a combination of lessons, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform. This is the first course of the Developing APIs with the Apigee API Platform series. After completing this course, enroll in the API Security with the Apigee API Platform course.

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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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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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在本入门级课程中，您将了解 Google Cloud 的基础工具和服务。此课程提供了可选视频， 旨在帮助您深入了解和回顾实验中涉及的概念。Google Cloud 基础知识是推荐给 Google Cloud 学员的第一门课程 - 即使您几乎没有云相关知识，也能从中获得实践 经验，并将其直接运用于您的首个 Google Cloud 项目。从编写 Cloud Shell 命令和部署您的第一个虚拟机，到在 Kubernetes Engine 上运行应用 或者使用负载均衡，“Google Cloud 基础知识”都是您了解该平台 基本功能的首选入门级课程。

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