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Zamir Arif

成为会员时间：2024

白银联赛

8674 积分
Streamline Application Development with Gemini CLI Earned Mar 23, 2026 EDT
优化智能体行为 Earned Feb 17, 2026 EST
使用智能体开发套件 (ADK) 打造您的首个智能体 Earned Feb 16, 2026 EST
智能体基础知识 Earned Feb 16, 2026 EST
Google Cloud 重要基础设施：核心服务 Earned Dec 22, 2025 EST
使用智能体开发套件 (ADK) 和 Agent Engine 部署多智能体系统 Earned Dec 1, 2025 EST
Google Cloud 基础知识：核心基础设施 Earned Nov 20, 2025 EST
云架构：设计、实施和管理 Earned Nov 18, 2025 EST
Preparing for your Professional Cloud Architect Journey Earned Nov 10, 2025 EST
开发 Google Cloud 网络 Earned Nov 9, 2025 EST
Networking in Google Cloud: Routing and Addressing Earned Nov 8, 2025 EST
Networking in Google Cloud: Network Architecture Earned Nov 8, 2025 EST
Networking in Google Cloud: Fundamentals Earned Nov 7, 2025 EST
生成式 AI 简介 Earned Nov 4, 2025 EST
Create and maintain Vertex AI Search data stores Earned Oct 22, 2025 EDT
Build search and recommendations applications with AI Applications Earned Oct 22, 2025 EDT
Create Data Stores for Gen AI Applications Earned Oct 20, 2025 EDT
Introduction to AI Applications Earned Oct 17, 2025 EDT

Complete the Streamline Application Development with Gemini CLI skill badge to demonstrate your proficiency in using the full capabilities of Gemini CLI in application development tasks. You will be tasked with defining multi-step plans, creating a reusable CLI extension, managing context, experimenting with checkpoints and deploying to Cloud Run all from Gemini CLI. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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您已经创建了自己的第一个智能体，现在是时候更进一步了。在本课程中，您将通过学习应用高级指令、模型选择、规划功能以及结构化输出模式来精进技能，将基础 AI 智能体升级为一个精确、专业的智能助理。加入社区论坛，提出问题并参与讨论

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使用 Google 的智能体开发套件 (ADK) 构建、配置和运行您的第一个 AI 智能体，将您对智能体的理解转化为实际应用。 在本实操课程中，您将设置一个完整的 ADK 开发环境，使用 Python 代码和 YAML 配置两种方式创建智能体，并通过多个界面运行智能体。您还将学习定义智能体行为的核心参数，将您在课程 1 中学到的知识应用到实际代码中。

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AI 智能体代表着超越传统大语言模型 (LLM) 的重大转变：AI 智能体不再仅仅只是生成基于文本的解决方案，更能自主行动来执行这些方案。 本课程将介绍 AI 智能体的基础知识、AI 智能体与 LLM API 的区别，以及 AI 智能体在现实世界中的价值所在。本课程基于 Google 的智能体白皮书，将为您提供必要的理论基础知识，以助您编写首行智能体代码 — 非常适合希望从自主、目标导向行为（而不仅仅是文本生成）的角度理解 AI 系统的开发者、架构师和技术决策者。 加入社区论坛，提出问题并参与讨论。

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这门自助式速成课程向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务，着重介绍了 Compute Engine。学员将通过一系列视频讲座、演示和动手实验，探索和部署各种解决方案元素，包括网络、系统和应用服务等基础架构组件。本课程的内容还包括如何部署实用的解决方案，包括客户提供的加密密钥、安全和访问权限管理、配额和结算，以及资源监控。

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在本课程中，您将学习如何使用 Google 智能体开发套件构建复杂的多智能体系统。您将构建搭载工具的智能体，利用父子层级关系和工作流进行连接，以此定义它们的交互方式。您将在本地运行智能体，将其部署到 Vertex AI Agent Engine 并作为托管式智能体流运行，基础设施决策和资源扩缩则由 Agent Engine 处理。请注意，这些实验基于此产品的预发布版本。在进行维护更新时，这些实验可能会出现一些延迟。

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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 云架构：设计、实施和管理课程，赢取技能徽章，展示您在以下方面的技能：使用 Apache Web 服务器部署可公开访问的网站；使用启动脚本配置 Compute Engine 虚拟机； 使用 Windows 堡垒主机和防火墙规则配置安全 RDP；构建 Docker 映像并将其部署到 Kubernetes 集群，然后进行更新；以及创建 CloudSQL 实例并导入 MySQL 数据库。 此技能徽章课程是非常有用的资源， 可帮助您理解 Google Cloud 认证 Professional Cloud Architect 认证考试中将会出现的主题。

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This course helps learners create a study plan for the PCA (Professional Cloud Architect) 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.

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完成开发 Google Cloud 网络课程，赢取技能徽章。在此课程中，您将学习 部署和监控应用的多种方法，包括执行以下任务的方法：探索 IAM 角色并添加/移除 项目访问权限、创建 VPC 网络、部署和监控 Compute Engine 虚拟机、 编写 SQL 查询、在 Compute Engine 中部署和监控虚拟机，以及使用 Kubernetes 通过多种部署方法部署应用。

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Welcome to the second course in the networking and Google Cloud series routing and addressing. In this course, we'll cover the central routing and addressing concepts that are relevant to Google Cloud's networking capabilities. Module one will lay the foundation by exploring network routing and addressing in Google Cloud, covering key building blocks such as routing IPv4, bringing your own IP addresses and setting up cloud DNS. In Module two will shift our focus to private connection options, exploring use cases and methods for accessing Google and other services privately using internal IP addresses. By the end of this course, you'll have a solid grasp of how to effectively route and address your network traffic within Google Cloud.

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Welcome to the third course of the "Networking in Google Cloud" series: Network Architecture! In this course, you will explore the fundamentals of designing efficient and scalable network architectures within Google Cloud. In the first module, Introduction to Network Architecture, we'll start by introducing you to the core components and concepts of network architecture, including subnets, routes, firewalls, and load balancing. Then in the second module, network topologies, we'll dive into various network topologies commonly used in Google Cloud, discussing their strengths, and weaknesses.

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Networking in Google cloud is a 6 part course series. Welcome to the first course of our six part course series, Networking in Google Cloud: Fundamentals.  This course provides a comprehensive overview of core networking concepts, including networking fundamentals, virtual private clouds (VPCs), and the sharing of VPC networks. Additionally, the course covers network logging and monitoring techniques. 

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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。

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Complete the Create and maintain Vertex AI Search data stores skill badge to demonstrate your proficiency in building various types of data stores used in Vertex AI Search applications. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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Complete the Build search and recommendations AI Applications skill badge to demonstrate your proficiency in deploying search and recommendation applications through AI Applications. Additionally, emphasis is placed on constructing a tailored Q&A system utilizing data stores. Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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Data stores represent a simple way to make content available to many types of generative AI applications, including search applications, recommendations engines, Gemini Enterprise apps, Agent Development Kit agents, and apps built with Google Gen AI or LangChain SDKs. Connect data from many sources include Cloud Storage, Google Drive, chat apps, mail apps, ticketing systems, third-party file storage providers, Salesforce, and many more.

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This course introduces AI Applications. You will learn about the types of apps that you can create using AI Applications, the high-level steps that its data stores automate for you, and what advanced features can be enabled for Search apps. (Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)

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