Prasanna Brabourame
成为会员时间：2026
钻石联赛
27897 积分
Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性
Earned Sep 15, 2026 EDT
使用智能体开发套件 (ADK) 和 Agent Engine 部署多智能体系统
Earned Sep 15, 2026 EDT
结合企业数据库构建 AI 智能体
Earned Sep 14, 2026 EDT
AgentOps：在 Google Cloud 上将 AI 智能体投入实际应用
Earned Sep 14, 2026 EDT
Orchestrate Workflows with the Data Agent Kit
Earned Sep 14, 2026 EDT
智能体策略：探索、设计和原型开发
Earned Sep 14, 2026 EDT
借助 Google Antigravity 快速起步：使用 AI 构建电子游戏
Earned Sep 13, 2026 EDT
了解 Google Cloud 智能体
Earned Sep 13, 2026 EDT
Google Cloud Agent Governance and Security
Earned Aug 31, 2026 EDT
Evaluate and Improve Agent Development Kit Agents
Earned Aug 30, 2026 EDT
部署多智能体架构
Earned Aug 30, 2026 EDT
Deploy an Agent with Agent Development Kit (ADK)
Earned Aug 30, 2026 EDT
Craft ADK Agents with Persistent Memories
Earned Aug 30, 2026 EDT
Cost Estimation and Optimization for Agentic Solutions
Earned Aug 30, 2026 EDT
Hill Climb Generative and Agentic Systems
Earned Aug 30, 2026 EDT
Upgrade to the Latest Gemini Models
Earned Aug 30, 2026 EDT
Evaluate Agents on Gemini Enterprise Agent Platform
Earned Aug 30, 2026 EDT
Evaluate Generative and Agentic Systems
Earned Aug 30, 2026 EDT
Build Enterprise Agents with Code Execution on Gemini Enterprise Agent Platform
Earned Aug 29, 2026 EDT
Build Agents with the Agent Development Kit
Earned Aug 29, 2026 EDT
Accelerate Development with Antigravity
Earned Aug 29, 2026 EDT
Build with the Managed Agents API on Gemini Enterprise Agent Platform
Earned Aug 29, 2026 EDT
Accelerate Agent Development with Antigravity and Agents CLI
Earned Aug 29, 2026 EDT
使用智能体开发套件 (ADK) 构建 AI 智能体
Earned Aug 27, 2026 EDT
Add Agents to Gemini Enterprise
Earned Aug 27, 2026 EDT
Govern Agent Access with Gemini Enterprise Agent Platform
Earned Aug 26, 2026 EDT
Secure your Agents with Gemini Enterprise Agent Platform
Earned Aug 26, 2026 EDT
Govern agents with Agent Gateway, Agent Registry, and Policies
Earned Aug 26, 2026 EDT
Deploy Gemini Enterprise with Workspace Data Sources and Model Armor
Earned Aug 26, 2026 EDT
Deploy the Gemini Enterprise app to Transform Enterprises
Earned Aug 26, 2026 EDT
Plan Change Management for Gemini Enterprise Deployments
Earned Aug 24, 2026 EDT
Model Armor：保障 AI 部署安全
Earned Aug 13, 2026 EDT
保护企业 AI 智能体
Earned Aug 12, 2026 EDT
将 Agent Skills 与多智能体系统搭配使用
Earned Aug 12, 2026 EDT
Build Agent Skills with Google
Earned Aug 12, 2026 EDT
使用 Gemini Enterprise 编排多智能体工作流
Earned Aug 12, 2026 EDT
以人为本的 AI
Earned Aug 12, 2026 EDT
使用 ADK 和 MCP 构建协作式多智能体系统
Earned Aug 11, 2026 EDT
部署您的第一个智能体
Earned Aug 11, 2026 EDT
在生产环境中构建和部署智能体
Earned Aug 11, 2026 EDT
使用 Gemini 和 Streamlit 开发生成式 AI 应用
Earned Aug 10, 2026 EDT
Google Cloud 云计算基础课程：Google Cloud 中的基础设施
Earned Jul 19, 2026 EDT
构建安全的 Google Cloud 网络
Earned Jul 19, 2026 EDT
在 Google Cloud 上设置应用开发环境
Earned Jul 19, 2026 EDT
为 Compute Engine 实现云负载均衡
Earned Jul 19, 2026 EDT
Google Cloud 云计算基础课程：云计算基础知识
Earned Jul 18, 2026 EDT
打造您的首个 Gemini Enterprise 应用
Earned Jul 16, 2026 EDT
企业智能体及其应用场景
Earned Jul 15, 2026 EDT
智能体基础知识
Earned Jul 15, 2026 EDT
优化智能体行为
Earned Jul 15, 2026 EDT
Add Agent Guardrails with Callbacks
Earned Jul 15, 2026 EDT
利用工具为智能体注入强大功能
Earned Jul 15, 2026 EDT
管理智能体记忆和状态
Earned Jul 15, 2026 EDT
Build a Certification Study Guide: PCA Exam Prep
Earned Jul 13, 2026 EDT
使用智能体开发套件 (ADK) 打造您的首个智能体
Earned Jul 13, 2026 EDT
适用于生成式 AI 的机器学习运维 (MLOps)
Earned Jul 1, 2026 EDT
生成式 AI 智能体：助力组织转型
Earned Jun 29, 2026 EDT
生成式 AI 应用：改变工作方式
Earned Jun 29, 2026 EDT
生成式 AI：不只是聊天机器人
Earned Jun 28, 2026 EDT
Create Data Stores for Gen AI Applications
Earned Jun 28, 2026 EDT
Introduction to AI Applications
Earned Jun 28, 2026 EDT
生成式 AI：剖析基本概念
Earned Mar 29, 2026 EDT
生成式 AI：全面了解生成式 AI
Earned Mar 29, 2026 EDT
Customer Experience Agent Studio：基础知识
Earned Mar 2, 2026 EST
Introduction to Gemini Enterprise for Customer Experience
Earned Mar 2, 2026 EST
Google Cloud 基础知识：核心基础设施
Earned Mar 1, 2026 EST
Create media search and media recommendations applications with AI Applications
Earned Feb 28, 2026 EST
Recommendations with AI Applications
Earned Feb 28, 2026 EST
Extend Gemini Enterprise Assistant Capabilities
Earned Feb 28, 2026 EST
Use a Third-Party Identity Provider with Workforce Identity Federation
Earned Feb 28, 2026 EST
[DEPRECATED] Introduction to NotebookLM
Earned Feb 28, 2026 EST
借助 Gemini Enterprise 加速知识交流
Earned Feb 28, 2026 EST
Configure AI Applications to optimize search results
Earned Feb 28, 2026 EST
Improve Agent Search Results on Agent Platform
Earned Feb 28, 2026 EST
Agent Search Analytics on Agent Platform
Earned Feb 28, 2026 EST
Agent Search UI configurations on Agent Platform
Earned Feb 28, 2026 EST
创建和管理 Bigtable 实例
Earned Feb 28, 2026 EST
Create and maintain Agent Search data stores
Earned Feb 26, 2026 EST
Build search and recommendations applications with AI Applications
Earned Feb 24, 2026 EST
Google Cloud 云计算基础课程面向几乎没有云计算背景或经验的人士。本课程概述了云计算基础知识、大数据和机器学习的核心概念，以及 Google Cloud 在其中的定位与应用方式。
完成本课程系列后，学员将能够阐述这些概念，并展示一定的实操技能。
课程应按以下顺序完成：
1. Google Cloud 云计算基础课程：云计算基础知识
2. Google Cloud 云计算基础课程：Google Cloud 中的基础设施
3. Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性
4. Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI
本课是第三门课程，介绍云端自动化和管理工具以及如何构建安全网络。
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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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使用 MCP Toolbox for Databases 构建可利用企业数据库的 AI 智能体。您将定义安全的数据库交互工具，并实现智能查询功能（利用向量嵌入、结构化查询）。
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了解将生成式 AI 智能体从原型设计阶段推进到生产阶段所需的 AgentOps 实践。本课程涵盖端到端可观测性、在 CI/CD 流水线中自动执行质量检查，以及保障智能体基础设施安全以实现企业合规性。探索 Gemini Enterprise Agent Ready (GEAR) 计划中的其他内容。
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This course brings AI-driven, natural-language data engineering into the IDE and CLI workflows you already use. Built on the Agent Development Kit (ADK), the Data Agent Kit connects to a wide array of Google Cloud services, including BigQuery, Spanner, BigLake, Dataproc, and Managed Airflow. By using it, you can collapse days of pipeline scaffolding, data build tool (dbt) authoring, and orchestration wiring into prompt-driven sessions.
As an intermediate-to-advanced practitioner, you will learn to build a data agent with the Agent Development Kit (ADK). You'll wire up the Model Context Protocol (MCP) layer, and use your agent to explore catalogs, transform data, train models, and orchestrate scheduled pipelines on Google Cloud.
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借助“智能体策略：探索、设计和原型开发”迈向未来本课程将带您掌握 Google 智能体 AI 转型框架，将传统的聊天机器人升级为能自主运转的得力助手。通过一个零售业用例，您将学习如何量化业务价值、确定 AI 项目的优先级、绘制关键用户历程，以及使用 Google AI Studio 和 Gemini Enterprise 等无代码工具构建功能性原型。本课程提供了一份坚实的路线图，帮助业务和技术负责人引领组织迈入智能体 AI 时代。
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在本课程中，您将学习如何在 Google Antigravity 中编排智能体，以极快的速度构建软件。在本实操课程中，您将首先学习如何安装和开始使用 Antigravity。接下来，您将使用 Firebase 为使用 Antigravity 构建的应用启用服务。最后，您将通过提示 Antigravity 中的智能体并行工作，来构建电子游戏《Voyager》。
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本课程全面概述了 Google Cloud 的智能体平台，包括 Vertex AI Agent Builder、Gemini Enterprise、Conversational Agents 和智能体开发套件。学员将了解每项产品的独特功能，区分具体应用场景的最佳解决方案，并获得有关创建搜索和聊天应用的基础知识。
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As enterprise teams transition to autonomous AI agents, security evolves toward proactive, identity-centric protection. In this course, you will implement a zero-trust security architecture for Cymbal Banking's underwriting platform using the Gemini Enterprise Agent Platform. By deploying a regional Egress Agent Gateway, configuring Model Armor and Semantic Governance (SGP) safety templates, assigning cryptographic SPIFFE identities to agent runtimes, and declaring a VPC-SC perimeter in Terraform, you will protect database boundaries and manage tools with production-grade governance.
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Complete the Evaluate and Improve Agent Development Kit Agents skill badge to demonstrate your ability to use ADK's evaluation tools to "hill climb" — making measurable, iterative improvements to an agent. You will run an initial evaluation to establish a baseline, apply optimization techniques, and re-evaluate the agent to measure your success.
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完成部署多智能体架构这一高级技能徽章课程，展示您在以下方面的技能： 使用 ADK 构建多智能体系统；通过 Agent-to-Agent (A2A) protocol 连接智能体， 通过 Model Context Protocol (MCP) 集成外部工具，并将完整的多智能体解决方案部署到 Agent Engine。
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In this challenge lab, you will demonstrate your ability to author agents using Agent Development Kit (ADK), deploy those agents to Agent Engine, and use them from a web app. Complete the challenge lab to earn a Google Cloud skill badge.
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This course explores architecting stateful AI agents that use short-term memory within a session or long-term memory services. Additionally, it covers giving agents existing expertise through skills. It details the core pillars of context engineering to facilitate personalized, continuous conversational experiences with expert agents.
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In this course, you’ll learn how to estimate and manage GenAI solution costs, focusing on the unique unit economics of AI versus traditional cloud billing. You will learn to:
Understand Metering: Master the four Google Cloud GenAI metering categories and the token economy driving costs.
Estimate Costs: Build defensible estimates using the Pricing Calculator for models, context caching, and agentic components.
Optimize Spend: Leverage controls—such as input/output token reduction, caching, RAG efficiency, and model routing—while balancing cost, quality, and latency.
Implement Governance: Apply FinOps best practices, including budgets, quotas, cost attribution, and Provisioned Throughput management to control spend.
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In this course, you'll learn the disciplined process of hill climbing to transform your generative and agentic systems into reliable, high-performing tools. You'll examine the iterative 8-step loop by diagnosing system failures through trajectory analysis and applying precise interventions across the model, prompt, tool, and framework layers. By the end of this course, you'll be prepared to optimize system architecture and automate the hill climbing cycle while balancing quality, cost, and latency as first-class metrics.
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In this course, you'll learn how to establish a rigorous upgrade regression testing pipeline, safely deploy models using A/B testing and/or shadow mode, and address legacy prompt technical debt. You'll also learn the latest about Gemini 3 parameters including thinking levels and thought signatures, as well as new capabilities like media resolution controls and streaming function calls.
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In this course, you learn to evaluate, diagnose, and optimize AI agents on the Gemini Enterprise Agent Platform (GEAP). You begin where most teams begin: the agent runs, but you have no eval cases, no test data, and no production traffic to grade it with. From there you follow the Quality Flywheel, the evaluate-analyze-optimize loop at the center of GEAP. You instrument the agent so it emits the telemetry GEAP reads, generate eval cases by simulation, choose the metrics that grade them, run offline evaluations, monitor live traffic and alert on quality drift, then cluster failures and optimize. A final module covers build-time evaluation with the Agent Development Kit (ADK), which runs on your machine before you deploy.
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Throughout this course, you'll learn how to establish rigorous evaluation criteria, perform evaluations, design objective rubrics, calibrate autoraters, and simulate evaluation data. You'll gain the skills needed to design, execute, and scale a comprehensive evaluation plan that aligns system capabilities with organizational KPIs. This course is designed for technical practitioners, machine learning engineers, and software architects who build and deploy generative and agentic applications.
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In this course, you explore the Code Execution feature of the Gemini Enterprise Agent Platform, which lets AI agents safely generate and run Python code in isolated sandbox environments. You learn how the Agent Sandbox fits into the broader platform architecture, how to configure and operate Code Execution sandboxes using the Agent Platform SDK, and how to integrate code execution into agent workflows with the Agent Development Kit (ADK).
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In this course, you'll learn to use the Agent Development Kit (ADK) to build systems where multiple AI agents collaborate on complex tasks. You'll start with the ADK agent model: how ADK represents agents, tools, and runners, and how a single agent is configured and run. You'll then make tools the model can call, persist session state across agents, and instrument the execution lifecycle with callbacks and plugins. Next, you'll orchestrate multiple agents using ADK's template workflow agents and graph-based workflows, and ground them in enterprise data through multi-source retrieval and MCP integrations. Finally, you'll deploy a multi-agent system to Agent Runtime as a managed service and register and share it through Gemini Enterprise so users across an organization can reach it.
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Complete the Accelerate Development with Antigravity skill badge to demonstrate your proficiency in using the Antigravity IDE for developing agentic workflows. You will be tasked with configuring an MCP server, authoring custom agent skills and rules, prototyping with the Agents CLI, and deploying to the Google Cloud Agent Runtime.
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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In this course, you'll learn to build and run enterprise agents on the Managed Agents API, the managed agent runtime on Gemini Enterprise Agent Platform. Three conceptual lessons give you the mental model. You'll learn why a real business task needs an agent rather than a chat model. You'll examine how the platform splits into a control plane that defines agents and a data plane that runs them. You'll learn how to assemble an agent from a definition, a sandboxed environment, mounted data, tools, and skills. And you'll learn how to run it with background interactions, a streamed reason-act loop, resilient typed results, and state that persists across turns. You then put that model to work in a hands-on lab, where you build, run, and harden a retail merchandising agent for Cymbal Retail from an empty project to a production-shaped deployment. By the end, you'll be able to design, build, and operate a managed agent of your own.
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In this course, you’ll learn to simplify the creation of autonomous enterprise agents using the Agent Development Kit (ADK) and you will learn how to leverage the power of Antigravity and the Agents CLI to transform your agent development workflow. In this course. You will explore practical techniques to automate repetitive tasks and significantly accelerate the creation of robust, enterprise-grade agents, ensuring scalability and efficiency in your AI projects.
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完成本课程，赢取使用智能体开发套件 (ADK) 构建 AI 智能体中级技能徽章，展示您在以下方面的技能： 提出实际的语言模型研究问题；构建一个简单的词元化器；制作用于训练 Transformer 语言模型的数据集；运行小语言模型的训练循环。
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In this challenge lab, you will demonstrate your ability to add agents to a Gemini Enterprise app. You will build an agent with Agent Designer. And you will build a no-code agent with Agent Development Kit, deploy it to Agent Engine, and add it to the Gemini Enterprise app.
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In this challenge lab, you will act as a cloud engineer supporting the Cymbal Pools finance team. Your mission is to deploy a BigQuery-enabled agent to Agent Runtime to help process invoice data using natural language.
Rather than building from scratch, you inherit an unsecured deployment. You must establish basic data governance by configuring the Agent Development Kit (ADK), deploying the agent with a dedicated SPIFFE identity, identifying permission blocks, and applying least-privilege IAM roles so the agent can safely query and update the BigQuery database from the Agent Runtime Playground.
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As organizations rapidly deploy AI workforces, securing these autonomous systems becomes paramount. Secure Your Agents with Gemini Enterprise Agent Platform is a practical, security-first course designed to help you establish centralized, zero-trust control and comprehensive visibility over your AI ecosystem.
Instead of relying on theoretical frameworks, this course teaches you how to defend AI agents the way they are actually attacked—layer by layer, with identity and access at the absolute foundation.
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This course covers the technical side of governing an AI agent workforce using Agent Gateway, Agent Registry, and Policies. It discusses the overall architecture of centralized agent governance, focusing on managing agent sprawl and securing communication with internal systems. The course explores the infrastructure and enterprise networking required to deploy the Agent Gateway, including automated deployment with Terraform and configuring private egress via Private Service Connect. It offers guidance towards establishing a zero-trust security perimeter using unique agent identities with mTLS, per-tool authorization with REQUEST_AUTHZ, and granular CEL policies. Furthermore, it empowers administrators to implement content security guardrails using Model Armor and Cloud DLP to mitigate semantic threats like prompt injection and data leakage. Finally, the course explains how to manage tool discovery through the Agent Registry and ensure end-to-end observability and threat detection using…
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In this challenge lab, you act as a Security Engineer deploying a secure Gemini Enterprise environment for Cymbal Bank. You will ground Gemini in web search and internal Workspace sources to ensure accurate, contextual responses. To maintain compliance, you will configure Model Armor policies to filter sensitive data and block threats like prompt injections and malicious URLs. Finally, you will manage specific end-user features to customize the AI experience safely
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This course covers the technical side of deploying the Gemini Enterprise app. It discusses the overall architecture of GE, decisions to be made when provisioning the app infrastructure, and integrating enterprise data via Data Stores, Connectors. and Actions. The course also explores the kinds of agents that can be added to Gemini Enterprise. It offers guidance towards establishing a security perimeter using IAM, VPC Service Control, Context-Aware Access, and semantic controls deployed with Model Armor. Finally, it empowers administrators to fine-tune the end-user experience through comprehensive configuration options, and explains how administrators keep AI deployments secure, compliant, and performant through OpenTelemetry instrumentation and prompt logging.
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This course will guide you through designing customer engagements that result in successful, well-utilized Gemini Enterprise deployments. Study the art of change management, how to identify and engage sponsors, recruit early adopters, help your customer identify and address cultural change challenges and skills gaps, and effectively deliver project communications. Additionally, learn how to support your customer to plan, offer, conduct, and evaluate end-user training, leverage partner resources, and create essential project documents.
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本课程回顾了 Model Armor 的基本安全功能，并让您能够使用该服务。您将了解与 LLM 相关的安全风险，以及 Model Armor 如何保护您的 AI 应用。
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了解如何在 Google Cloud 上保护和治理 AI 智能体。本课程提供了一个实用的路线图，可帮助您保护智能体记忆，通过 IAM 和 VPC Service Controls 实施严格的访问权限控制，并部署实时对话防护措施，从而确保企业部署安全合规。
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完成高级技能徽章课程将 Agent Skills 与多智能体系统搭配使用，以展示以下技能：使用 ADK 构建多智能体系统、通过智能体到智能体 (A2A) 协议连接智能体、使用 Model Context Protocol (MCP) 集成外部工具以及将完整的多智能体解决方案部署到 Agent Engine。 探索 Gemini Enterprise Agent Ready (GEAR) 计划中的其他内容。
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Close the gap between general AI capabilities and your domain knowledge through Agent Skills. This course walks you through the full lifecycle of custom skill building, from local scaffolding and testing to enterprise scaling and sharing using Google's agent ecosystem, including Google Antigravity, ADK, and Skill Registry. Additionally, you use Google Agents CLI toolkit to attach skills to standalone 24/7 cloud agents, equipping your team with reliable, autonomous digital coworkers.
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完成入门级使用 Gemini Enterprise 编排多智能体工作流技能徽章课程，展示您在以下方面的技能：使用由 Gemini Enterprise 提供支持的智能体助理整合来自第一方和第三方来源的数据、制作多媒体营销材料，以及跨系统自动执行业务操作。
技能徽章通过动手实验和挑战赛形式的评估，检验您对特定产品的实际知识掌握情况。完成课程即可获得徽章，也可直接参加实验室挑战赛，快速获得徽章。徽章可证明您掌握技能的熟练程度，提升您的专业形象，最终助您获得更多职业机会。欢迎访问您的个人资料，跟踪您已获得的徽章。
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探索从任务驱动型工作流到以人为本的 AI 编排的重大转变。您将学习如何从战略层面区分增强和自动化，以及如何平衡机器效率与人类直觉。
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学习如何使用 Google 的智能体开发套件 (ADK) 和 Model Context Protocol (MCP) 设计、协调和部署多智能体系统。以旅行礼宾为例，您将学习如何编排由专用智能体组成的网络，并为其配置自定义护栏。学完本课程后，您将了解构建稳健、可伸缩的 AI 工作流所需的设计模式和部署策略。
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将智能体从 localhost 部署到生产环境。本课程将介绍如何将 ADK 智能体部署到 Vertex AI Agent Engine 和 Cloud Run，以及如何通过记忆库实现可选的跨会话记忆功能。
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探索如何使用 Google 的智能体开发套件 (ADK) 和 Google Cloud 强大的基础设施来构建和部署多智能体系统。您将学习如何设计分层智能体树和确定性工作流智能体，同时确定理想的托管环境（从无服务器 Cloud Run 到高性能 GKE），以确保您的 AI 智能体安全、可伸缩且可用于生产用途。
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完成中级技能徽章课程“使用 Gemini 和 Streamlit 开发生成式 AI 应用”，展示您在以下方面的技能： 文本生成、通过 Python SDK 和 Gemini API 应用函数调用，以及通过 Cloud Run 部署 Streamlit 应用。 您将了解如何以不同方式通过提示来让 Gemini 生成文本、使用 Cloud Shell 进行测试，以及如何迭代 Streamlit 应用，随后将其封装成 Docker 容器并部署在 Cloud Run 中。
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Google Cloud 云计算基础课程面向云计算零基础或经验较少的人群。本课程概述了云计算基础知识、大数据和机器学习的核心概念，以及 Google Cloud 在其中的定位与应用方式。
完成本系列课程后，学员将能够清晰阐述这些概念，并掌握部分实操技能。
课程应按以下顺序完成：
1. Google Cloud 云计算基础课程：云计算基础知识
2. Google Cloud 云计算基础课程：Google Cloud 中的基础设施
3. Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性
4. Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI
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完成构建安全的 Google Cloud 网络课程，赢取技能徽章。在此课程中，您将了解与网络有关的众多 资源，以便在 Google Cloud 上构建、扩缩和保护自己的应用。
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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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Google Cloud 云计算基础课程面向云计算零基础或经验较少的人群。本课程概述了云计算基础知识、大数据和机器学习的核心概念，以及 Google Cloud 在其中的定位与应用方式。
完成本系列课程后，学员将能够清晰阐述这些概念，并掌握部分实操技能。
课程应按以下顺序完成：
1. Google Cloud 云计算基础课程：云计算基础知识
2. Google Cloud 云计算基础课程：Google Cloud 中的基础设施
3. Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性
4. Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI
本课是第一门课程，概述了云计算、Google Cloud 的使用方式以及各种计算选项。
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打造您的首个 Gemini Enterprise 应用，赢得技能徽章！将各种数据源连接到您的应用中，构建强大、统一的搜索和分析引擎。掌握进阶能力，如：深度研究型智能体、多智能体协同构思，以及用于进行聚焦式分析的 NotebookLM。
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了解 AI 智能体如何为业务带来实际影响。您将把智能体类型关联到您的关键绩效指标 (KPI)，并探索能够解决实际瓶颈的用例。然后，您将了解 Gemini Enterprise 如何帮助您构建和编排合适的智能体，其范围涵盖从无代码到高代码的各种解决方案。
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本课程将介绍 AI 智能体的基础知识，并探讨智能体在现实世界中的价值所在。它为想要从自主、目标导向行为的角度理解 AI 系统的开发者、架构师和技术决策者奠定了基础。
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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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You’ve built capable agents with powerful tools—now ensure they operate safely and reliably. Use callbacks as observation points and control mechanisms. Monitor what’s happening, validate inputs and outputs, implement guardrails, and gain confidence that your agents behave in production.
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您已经构建了具有高级配置的智能体，现在可赋予它们实际应用能力。为智能体配备能够搜索网络、执行代码、查询数据库和执行自定义操作的工具。让智能体从“智能回答者”转变为能够自主采取行动的得力助手。
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您已经构建了能够回答查询的基本 LLM 智能体，现在让我们为其赋予状态。使用会话状态来构建能够维护上下文、记住用户偏好并提供个性化体验的智能体。将智能体从“无状态的回复者”转变为“智能助理”。
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Architect 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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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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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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“生成式 AI 智能体：助力组织转型”是“Gen AI Leader”学习路线中的第五门课程，也是最后一门课程。本课程探讨了组织如何使用量身定制的生成式 AI 智能体，帮助应对特定的业务挑战。您将亲自动手构建一个基本的生成式 AI 智能体，并探索这些智能体的组成部分，例如模型、推理循环以及各种工具。
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“生成式 AI 应用：改变工作方式”是 Generative AI Leader 学习路线的第四门课程。本课程介绍 Google 的生成式 AI 应用，例如 Gemini for Workspace 和 NotebookLM。它将引导您逐一了解接地、检索增强生成、构建有效提示和构建自动化工作流等概念。
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生成式 AI：不只是聊天机器人是 Gen AI Leader 学习路线的第一门课程，没有前提条件要求。本课程旨在带您超越对聊天机器人的浅层认知，深入挖掘生成式 AI 为您的组织带来的真正潜力。您将探索基础模型和提示工程等概念，它们对于利用生成式 AI 的强大功能至关重要。本课程还将提供指导，让您了解在为组织制定成功的生成式 AI 策略时，应考虑哪些重要因素。
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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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生成式 AI：剖析基本概念是“Gen AI Leader”学习路线的第二门课程。在本课程中，您将探索 AI、机器学习和生成式 AI 之间的差异，了解各种数据类型如何赋能生成式 AI 来应对业务挑战，从而了解生成式 AI 的基本概念。您还将深入了解 Google Cloud 应对基础模型局限性的策略，以及负责任和安全的 AI 开发与部署面临哪些关键挑战。
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“生成式 AI：全面了解生成式 AI”是“Gen AI Leader”学习路线中的第三门课程。生成式 AI 正在改变我们的工作方式以及与世界的互动方式。作为领导者，应该如何利用生成式 AI 来推动实际业务成果？在本课程中，您将探索构建生成式 AI 解决方案的不同层级、Google Cloud 的产品/服务，以及选择解决方案时需要考虑的因素。
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本课程旨在让对话设计师和构建者掌握相关概念和实用技能，以便使用 Customer Experience Agent Studio (CX Agent Studio) 设计、构建和测试复杂的多智能体多模态客户体验智能体。
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This course explores the different products and capabilities of Gemini Enterprise for Customer Experience, including CX Agent Studio, Agent Assist and CX Insights. Additionally, it covers the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel.
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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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Complete the Create media search and media recommendations applications with AI Applications skill badge to demonstrate your ability to create, configure, and access media search and recommendations applications using AI Applications.
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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Do you want to keep your users engaged by suggesting content they'll love?
This course equips you with the skills to build a cutting-edge recommendations app using your own data with no prior machine learning knowledge. You learn to leverage AI Applications to build recommendation applications so that audiences can discover more personalized content, like what to watch or read next, with Google-quality results customized using optimization objectives.
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Complete the Extend Gemini Enterprise Assistant Capabilities skill badge to demonstrate your ability to extend Gemini Enterprise assistant's capabilities with actions, grounding with Google Search, and a conversational agent.
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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This course provides learners the knowledge to configure Workforce Identity Federation to grant Google Cloud and Gemini Enterprise access to users that authenticate using a third-party Identity Provider. The curriculum includes theory and demo videos covering workforce identity pools, OIDC and SAML providers, attribute mapping, IAM policies, and troubleshooting guidance.
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NotebookLM is an AI-powered collaborator that helps you do your best thinking. After uploading your documents, NotebookLM becomes an instant expert in those sources so you can read, take notes, and collaborate with it to refine and organize your ideas.
NotebookLM Pro gives you everything already included with NotebookLM, as well as higher utilization limits, access to premium features, and additional sharing options and analytics.
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Gemini Enterprise 结合了 Google 在搜索和 AI 领域的专长。它是一款强大的工具，让员工只需通过一个搜索栏，就能从文档库、邮件、聊天消息、工单系统及其他数据源中查找具体信息。Gemini Enterprise 助理还能帮助进行头脑风暴、开展研究、生成文档大纲并执行其他操作，比如邀请同事参加某个日历活动。因此它能加快知识型工作的进度并提升协作效率。（请注意，Gemini Enterprise 以前称为 Google Agentspace，本课程中可能会提及以前的产品名称。）
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Complete the Configure AI Applications to optimize search results skill badge to demonstrate your proficiency in configuring search results from AI Applications. You will be tasked with implementing search serving controls to boost and bury results, filter entries from search results and display metadata in your search interface.
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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This course covers techniques for boosting and filtering search results, as well as the implementation of meta tags for advanced search control.
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AI Applications provides built-in analytics for your Agent Search and Gemini Enterprise apps. Learn what metrics are tracked and how to view them in this course.
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Initial deployment of Agent Search and Gemini Enterprise apps takes only a few clicks, but getting the configurations right can elevate a deployment from a basic off-the-shelf app to an excellent custom search or recommendations experience.
In this course, you'll learn more about the many ways you can customize and improve search, recommendations, and Gemini Enterprise apps.
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完成入门级技能徽章课程创建和管理 Bigtable 实例，展示以下方面的技能：创建实例、设计架构、 查询数据，以及在 Bigtable 中执行管理任务，包括监控性能、配置节点自动扩缩和复制。
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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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