Architecting with Google Kubernetes Engine: Foundations - 简体中文
Earned Apr 26, 2024 EDT
DEPRECATED BigQuery for Data Warehousing
Earned Feb 16, 2024 EST
Preparing for your Professional Cloud Architect Journey
Earned Feb 15, 2024 EST
Smart Analytics - Implementing Dataplex
Earned Feb 15, 2024 EST
使用 Dataplex 构建数据网格
Earned Feb 2, 2024 EST
Dataplex 使用入门
Earned Jan 30, 2024 EST
Getting Started With Application Development
Earned Jan 19, 2024 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud
Earned Jan 17, 2024 EST
适用于端到端 SDLC 的 Gemini
Earned Jan 15, 2024 EST
适用于 DevOps 工程师的 Gemini
Earned Jan 15, 2024 EST
适用于网络工程师的 Gemini
Earned Jan 15, 2024 EST
Achieving Advanced Insights with BigQuery
Earned Jan 15, 2024 EST
在 Google Cloud 上为机器学习 API 准备数据
Earned Jan 11, 2024 EST
利用 BigQuery ML 构建预测模型时的数据工程处理
Earned Jan 10, 2024 EST
面向数据科学家和分析师的 Gemini
Earned Jan 10, 2024 EST
适用于安全工程师的 Gemini
Earned Jan 10, 2024 EST
Google 幻灯片中的 Gemini
Earned Jan 8, 2024 EST
适用于应用开发者的 Gemini
Earned Jan 8, 2024 EST
Gemini for Google Workspace 简介
Earned Jan 8, 2024 EST
Gmail 中的 Gemini
Earned Jan 8, 2024 EST
Google 文档中的 Gemini
Earned Jan 8, 2024 EST
Google 表格中的 Gemini
Earned Jan 8, 2024 EST
适用于云架构师的 Gemini
Earned Jan 8, 2024 EST
使用 BigQuery 构建数据仓库
Earned Jan 5, 2024 EST
Serverless Data Processing with Dataflow: Foundations
Earned Jan 4, 2024 EST
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Jan 3, 2024 EST
Building Batch Data Pipelines on Google Cloud
Earned Dec 18, 2023 EST
Responsible AI: 和 Google Cloud 一起践行 AI 原则
Earned Dec 14, 2023 EST
负责任的 AI 简介
Earned Dec 13, 2023 EST
Modernizing Data Lakes and Data Warehouses with Google Cloud
Earned Dec 12, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Nov 8, 2023 EST
Preparing for your Professional Data Engineer Journey
Earned Sep 29, 2023 EDT
在 Vertex AI 上构建和部署机器学习解决方案
Earned Jun 15, 2023 EDT
开发 Google Cloud 网络
Earned Jun 1, 2023 EDT
Certification Learning Path: Professional Cloud DevOps Engineer
Earned May 30, 2023 EDT
使用 Google Cloud Observability 进行监控和记录
Earned May 29, 2023 EDT
在 Google Cloud 中实施 DevOps 工作流
Earned May 26, 2023 EDT
DEPRECATED Cloud Operations and Service Mesh with Anthos
Earned May 25, 2023 EDT
可靠的 Google Cloud 基础设施: 设计和流程
Earned May 24, 2023 EDT
Developing a Google SRE Culture
Earned May 19, 2023 EDT
Logging and Monitoring in Google Cloud
Earned May 18, 2023 EDT
从 BigQuery 数据中挖掘数据洞见
Earned Feb 9, 2023 EST
Launching into Machine Learning
Earned Feb 9, 2023 EST
通过 BigQuery ML 创建机器学习模型
Earned Jan 27, 2023 EST
为 Looker 信息中心和报告准备数据
Earned Jan 27, 2023 EST
Applying Machine Learning to your Data with Google Cloud
Earned Jan 26, 2023 EST
面向机器学习的 BigQuery
Earned Jan 25, 2023 EST
Google Cloud 重要基础设施：核心服务
Earned Nov 22, 2022 EST
Getting Started with Terraform for Google Cloud
Earned Nov 21, 2022 EST
在 Google Cloud 上使用 Terraform 构建基础设施
Earned Oct 4, 2022 EDT
在 Compute Engine 上实现负载均衡
Earned Oct 3, 2022 EDT
Google Cloud Essentials
Earned Oct 3, 2022 EDT
在 Google Cloud 上设置应用开发环境
Earned Aug 5, 2022 EDT
Scaling with Google Cloud Operations
Earned Aug 4, 2022 EDT
Google Kubernetes Engine 使用入门
Earned Aug 4, 2022 EDT
Exploring Data Transformation with Google Cloud
Earned Jul 25, 2022 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned Jul 25, 2022 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned Jul 20, 2022 EDT
Google Cloud 基础知识：核心基础设施
Earned Jul 19, 2022 EDT
Digital Transformation with Google Cloud
Earned Jul 11, 2022 EDT
This course was designed to prepare Google Workspace Administrators to troubleshoot common Google Workspace issues. Learners will practice diagnosing and resolving problems in Gmail, Calendar, and Drive, and navigating the Admin console. They will also experience analyzing audit logs to troubleshoot security issues, and gathering information and using available resources to troubleshoot and report technical issues.
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在本课程中，您将学习如何使用 Google 的可移植 UI 工具包 Flutter 来开发应用，并将开发的应用与 Google 的生成式 AI 模型家族 Gemini 相集成。您还将练习使用 Vertex AI Agent Builder，这是 Google 为构建和管理 AI 智能体及应用而提供的平台。
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Earn a skill badge by completing the Integrate BigQuery Data and Google Workspace using Apps Script quest, where you learn ways to connect Workspace products with BigQuery by using App Sheet. 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 this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Complete the Evaluate Gen AI model and agent performance skill badge to demonstrate your ability to use the Gen AI evaluation service. You will evaluate models to select the best model for a given task, compare models against each other and evaluate the performance of agents.
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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Evaluation is important at every step of your Gen AI development process. In this course you will learn how to evaluate gen AI agents built using agent frameworks.
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Learn how to create Hybrid Search applications using Vertex AI Vertex Search to combine semantic searching with keyword search to return results based on both semantic meaning and keyword matching.
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Learn how to build your own Retrieval-Augmented Generation (RAG) solutions for greater control and flexibility than out-of-the-box implementations. Create a custom RAG solution using Vertex AI APIs, vector stores, and the LangChain framework.
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本课程探讨 BigQuery 中用于减轻 AI 幻觉的检索增强生成 (RAG) 解决方案。BigQuery 引入了 RAG 工作流，其中涵盖了创建嵌入、搜索向量空间和生成更优质的回答。本课程解释了这些步骤背后的概念原理，以及这些步骤在 BigQuery 中的实际实施过程。学完本课程后，学员将能够使用 BigQuery 和生成式 AI 模型（如 Gemini）以及嵌入模型来构建 RAG 流水线，以解决在具体情况下遇到的 AI 幻觉问题。
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This lab tests your ability to develop a real-world Generative AI Q&A solution using a RAG framework. You will use Firestore as a vector database and deploy a Flask app as a user interface to query a food safety knowledge base.
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Complete the Edit images with Imagen skill badge to demonstrate your skills with Imagen's mask modes and editing modes to edit images according to certain prompts.
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 Develop solutions using Model Garden APIs skill badge to demonstrate your ability to use Vertex AI Model Garden features when building gen AI solutions. You will use partner APIs such as Anthropic Claude ands Meta Llama, deploy and programatically access foundation models like Gemma and Stable Diffusion XL and access Vertex AI Endpoints.
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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Model Garden is a model library that helps you discover, test, and deploy models from Google and Google partners. Learn how to explore the available models and select the right ones for your use case. And how to deploy and interact with Model Garden models through the Google Cloud console and APIs.
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Model tuning is an effective way to customize large models to your tasks. It's a key step to improve the model's quality and efficiency. Model tuning provides benefits such as higher quality results for your specific tasks and increased model robustness. You learn some of the tuning options available in Vertex AI and when to use them.
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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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Generate engaging media with Google's foundation models for media. Create new images with Imagen, or edit your existing photos by adding details or outpainting to create a wider view. Replace backgrounds to put your products in new scenes. And learn the basics of generating videos with Veo!
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An LLM-based application can process language in a way that resembles thought. But if you want to extend its capabilities to take actions by running other functions you have coded, you will need to use function calling. This can also be referred to as tool use. Additionally, you can give a model the ability to search Google or search a data store of documents to ground its responses. In other words, to base its answers on that information. In this course, you’ll explore these concepts.
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Learn a variety of strategies and techniques to engineer effective prompts for generative models
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Learn how to leverage Gemini multimodal capabilities to process and generate text, images, and audio and to integrate Gemini through APIs to perform tasks such as content creation and summarization.
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Complete the Extend Gemini with controlled generation and Tool use skill badge to demonstrate your proficiency in connecting models to external tools and APIs. This allows models to augment their knowledge, extend their capabilities and interact with external systems to take actions such as sending an email.
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 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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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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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 Google Agentspace assistant capabilities skill badge to demonstrate your ability to extend Google Agentspace 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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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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AI Applications provides built-in analytics for your Vertex AI Search and Google Agentspace apps. Learn what metrics are tracked and how to view them in this course.
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Initial deployment of Vertex AI Search and Google Agentspace 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 Google Agentspace apps.
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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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If you've worked with data, you know that some data is more reliable than other data.
In this course, you'll learn a variety of techniques to present the most reliable or useful results to your users. Create serving controls to boost or bury search results. Rank search results to ensure that each query is answered by the most relevant data. If needed, tune your search engine. Learn to measure search results to ensure your search applications deliver the best possible results to each user.
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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, Google Agentspace 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.
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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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Complete the Leverage best practices for developing, operating, and securing production-grade Conversational Agents skill badge to demonstrate your ability to implement a variety of best practices around development, deployment, and security. These will include: Using versions and environments, backing up with Git integration, leveraging test cases and CI/CD testing, tracking conversations with conversation history and logging, redacting data, and securing acceess to agent and webhook endpoints.
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 develope…
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This course will equip you with the tools to develop complex conversational experiences in Conversational Agents using best practices to create production-ready agents.
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In this course you will learn the key architectural considerations that need to be taken into account when designing for the implementation of Conversational AI solutions. Please note Dialogflow CX was recently renamed to Conversational Agents and CCAI Insights was renamed to Conversational Insights.
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In this course, you will learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.
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This course explores the fundamentals of the feedback loop process for Conversational Agent development and introduces the native capabilities within Conversational Agents that support it. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational Agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, Virtual Agent, and CCAI Insights.
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In this course you will learn how Conversational AI Agent Assist can help distill complex customer interactions into concise and clear summaries. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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In this course you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the voice channel, as well as the options available for integration with other platforms in the Conversational AI ecosystem.
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In this course you will learn how to leverage Conversational Insights to uncover hidden information from your contact center data to increase operational efficiency and drive data-driven business decisions. Please note Contact Center AI Insights were recently renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product name for Contact Center AI Insights.
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Complete the Analyze patterns in conversational data with Conversational Insights skill badge to demonstrate your proficiency in analysing customer conversations with Conversational Insights. After completing this challenge, you will be ready to deploy Conversation Insights to improve customer service performance, and create better customer experiences.
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 will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the chat channel.
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Complete the Improve customer and agent satisfaction with Agent Assist skill badge to demonstrate your proficiency in configuring basic conversational agents that can escalate actions to human agents, and configuring Agent Assist to help human agents with customer queries. You prove your knowledge in configuring Generators for summarization, classification and recommendation of tickets as well leverage tools such as Generative Knowledge Assist, to provide further context to human agents.
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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Learn about building conversational AI voice and chat integrations, including how telephony systems can connect with Google to enable phone-based interactions within the Conversational AI ecosystem. Explore key topics such as the differences between chat and voice conversations, the writing process for creating conversation scripts, and the beginning of the interrogative series and closing sequence.
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Complete the Extend agent functionality with Webhooks, Tools, and Integrations skill badge to demonstrate your ability to let conversational agents take actions. You will create a flow that calls a webhook and a playbook with a tool and combine them into a hybrid agent. You'll also prepare custom payload for rich content experiences in the Conversational Messenger.
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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Connect Conversational Agents to external systems and APIs to expand what agents can do, designing an end-to-end system that is resilient, fault-tolerant and secure.
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In this course, you'll learn to develop generative agents that answer questions using websites, documents, or structured data. You will explore Vertex AI Applications and understand the advantages of data store agents, including their scalability and security.
You'll learn about different data store types and also discover how to connect data stores to agents and add personalization for enhanced responses.
Finally, you'll gain insights into common search configurations and troubleshooting techniques.
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Explore the Generative AI features for Conversational Agents and how to incorporate them into stateful Flows.
Discover the possibilities with Generators, Generative Fallback, and Data Stores, as well as best practices and security settings for using these features.
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Discover flows in Conversational Agents and learn how to build deterministic chat and voice experiences with language models. Explore key concepts like drivers, intents, and entities, and how to use them to create conversational agents.
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Explore Playbooks and their implementation of the ReAct pattern for building Conversational Agents. You will learn how to construct a Playbook, set up goals and instructions to build a chatbot in natural language, and learn to test and deploy your solution.
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This course explores the different products and capabilities of Customer Engagement Suite (CES) and Conversational agents. 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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Complete the Build basic Conversational Agents with Playbooks and Flows skill badge to demonstrate your proficiency in building virtual agents using traditional NLU and generative-based features.
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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本课程介绍 AI 隐私保护和安全方面的重要主题，还将探索使用 Google Cloud 产品和开源工具实施建议的 AI 隐私保护和安全实践的实用方法和工具。
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本课程介绍了 AI 可解释性和透明度的相关概念，探讨了 AI 透明度对于开发者和工程师的重要性。同时探索了有助于在数据和 AI 模型中实现可解释性和透明度的实用方法及工具。
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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。
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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这是一节入门级微学习课程，探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能，还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。
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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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This course equips learners with skills to govern data within their Google Workspace environment. Learners will explore data loss prevention rules in Gmail and Drive to prevent data leakage. They will then learn how to use Google Vault for data retention, preservation, and retrieval purposes. Next, they will learn how to configure data regions and export settings to align with regulations. Finally, learners will discover how to classify data using labels for enhanced organization and security.
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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools.
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Gen AI: Navigate the Landscape is the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.
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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.
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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.
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This course was designed to give learners a comprehensive understanding of Google Workspace core services. Learners will explore enabling, disabling, and configuring settings for these services, including Gmail, Calendar, Drive, Meet, Chat, and Docs. Next, they'll learn how to deploy and manage Gemini to empower their users. Finally, learners will examine use cases for AppSheet and Apps Script to automate tasks and extend the functionality of Google Workspace applications.
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Agentspace 结合了 Google 在搜索和 AI 领域的专长。它是一款企业工具，让员工只需通过一个搜索栏，就能从文档库、电子邮件、聊天消息、工单系统及其他数据源中查找具体信息。Agentspace 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。
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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.
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Complete the introductory Build LookML Objects in Looker skill badge to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements.
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In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
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This course explores how to leverage Looker to create data experiences and gain insights with modern business intelligence (BI) and reporting.
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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
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完成在 Google Cloud 上实施云安全基础措施技能徽章中级课程， 展示自己在以下方面的技能：使用 Identity and Access Management (IAM) 创建和分配角色； 创建和管理服务账号；跨虚拟私有云 (VPC) 网络实现专用连接； 使用 Identity-Aware Proxy 限制应用访问权限； 使用 Cloud Key Management Service (KMS) 管理密钥和加密数据；创建专用 Kubernetes 集群。 技能徽章是由 Google Cloud 颁发的专有数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能 徽章课程和作为最终评估的实验室挑战赛，即可获得技能徽章， 并在您的社交圈中秀一秀自己的能力。
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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。
在本次课程中，探索 AI 赋能的搜索技术、工具和应用。学习利用向量嵌入的语义搜索、融合语义和关键字的混合搜索方法，以及检索增强生成 (RAG) 技术，以打造基于事实的 AI 智能体，尽可能减少 AI 幻觉。获取 Vertex AI Vector Search 实战经验，打造您自己的智能搜索引擎。
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Earn a skill badge by completing the Get Started with Eventarc skill badge course, where you use Eventarc to create event triggers for different resources including Pub/Sub topics and Cloud Storage buckets.
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Earn a skill badge by completing the Cloud Run functions: 3 Ways course, where you learn how to use Cloud Run functions through the Google Cloud console and on the command line. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services. It tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge course, including the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Earn a skill badge by completing the Create a Streaming Data Lake on Cloud Storage course, where you use Pub/Sub, Dataflow, and Cloud Storage together to create a streaming data lake on Google Cloud. 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 this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
Earn a skill badge by completing the Use APIs to Work with Cloud Storage quest, where you learn how APIs work in Google, and how to use the Cloud Storage API specifically. 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 this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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完成Google Cloud 云计算基础知识挑战任务，赢取技能徽章。 您将学习如何在 Compute Engine 中使用虚拟机 (VM)、永久性 磁盘和 Web 服务器。 技能徽章是一种专有数字徽章， 由 Google Cloud 颁发，旨在认可您已熟悉特定的 Google Cloud 产品与服务， 并在交互式实操环境中证明了运用所学知识 的能力。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得相应的数字徽章，在您的人际圈中秀出自己的技能。
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Earn a skill badge by completing the Tag and Discover BigLake Data quest, where you use BigQuery, BigLake, and Data Catalog within Dataplex to create, tag, and discover BigLake tables. 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 this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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完成 BigQuery 流式数据分析挑战任务，赢取技能徽章 。在此挑战任务中，您将结合使用 Pub/Sub、Dataflow 和 BigQuery 来流式传输 数据以进行分析。 技能徽章是由 Google Cloud 颁发的专属数字徽章， 旨在认可您在 Google Cloud 产品与服务方面的熟练度。 您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后 才能获得。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得相应的数字徽章，在您的人际圈中秀出自己的技能。
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Earn a skill badge by completing the Secure BigLake Data quest, where you use IAM, BigQuery, BigLake, and Data Catalog within Dataplex to create and secure BigLake tables. 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 this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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This skill badge aims to provide partners an introduction to BigQuery Data Transfer Service and Migration Service, two powerful tools for managing and migrating data in the cloud. Learners will learn how to leverage these tools to efficiently migrate and manage data, and gain hands-on experience through labs.
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Earn a skill badge by completing the Get Started with Cloud Storage quest, where you learn how to create a Cloud Storage bucket, how to use the Cloud Storage command line, and how to use Bucket Lock to protect objects in a bucket. 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 this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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完成 Pub/Sub 使用入门挑战任务，赢取技能徽章。 您将学习如何通过 Cloud 控制台使用 Pub/Sub，如何使用 Cloud Scheduler 安排 作业以节省工作量，以及 Pub/Sub Lite 如何在有大量 事件注入的场景中节省费用。 技能徽章是一种专属数字徽章， 由 Google Cloud 颁发，旨在认可您已熟悉特定的 Google Cloud 产品与服务， 并在交互式实操环境中证明了运用所学知识 的能力。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得相应的数字徽章，在您的人际圈中秀出自己的技能。
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完成 API Gateway 使用入门挑战任务，赢取技能徽章。 您将学习如何通过全托管式网关，使用 API Gateway 来部署、保护和管理 API 。 技能徽章是由 Google Cloud 颁发的专属数字徽章， 旨在认可您在 Google Cloud 产品与服务方面的熟练度。 您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后 才能获得此徽章。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得数字徽章，在您的人际圈中秀出自己的技能。
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This course was designed to provide an understanding of user and resource management in Google Workspace. Learners will explore the configuration of organizational units to align with their organization's needs. Additionally, learners will discover how to manage various types of Google Groups. They will also develop expertise in managing domain settings within Google Workspace. Finally, learners will master the optimization and structuring of resources within their Google Workspace environment.
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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series.
In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area.
You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training.
This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.
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This course empowers learners to secure their Google Workspace environment. Learners will implement strong password policies and two-step verification to govern user access. They will then utilize the security investigation tool to proactively identify and respond to security risks. Next, they will manage third-party app access and mobile devices to ensure security. Finally, learners will enforce email security and compliance measures to protect organizational data.
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Earn a skill badge by completing the Configure your Workplace: Google Workspace for IT Admins quest, where you will get try out the Admin role for Workspace and learn to provision Groups, manage applications, security, and manage Meet. 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 skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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完成 在 Vertex AI 中设计提示入门技能徽章课程，展示以下方面的技能： Vertex AI 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。 技能徽章 是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能 徽章课程和作为最终评估的实验室挑战赛，获得技能徽章， 并在您的社交圈中秀一秀自己的水平。
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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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本课程介绍 Vertex AI Studio，这是一种用于与生成式 AI 模型交互、围绕业务创意进行原型设计并在生产环境中落地的工具。通过沉浸式应用场景、富有吸引力的课程和实操实验，您将探索从提示到产品的整个生命周期，了解如何将 Vertex AI Studio 用于多模态 Gemini 应用、提示设计、提示工程和模型调优。本课程的目的在于帮助您利用 Vertex AI Studio，在自己的项目中充分发掘生成式 AI 的潜力。
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本课程介绍 Google Cloud 中的 AI 和机器学习 (ML) 服务，这些服务可构建预测式和生成式 AI 项目。本课程探讨从数据到 AI 的整个生命周期中可用的技术、产品和工具，包括 AI 基础、开发和解决方案。通过引人入胜的学习体验和实操练习，本课程可帮助数据科学家、AI 开发者和机器学习工程师提升技能和知识水平。
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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。 技能徽章是由 Google Cloud 颁发的专有数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛，即可获得技能徽章， 在您的人际圈中炫出自己的技能。
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This third course covers cloud automation and management tools and building secure networks.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This first course provides an overview of cloud computing, ways to use Google Cloud, and different compute options.
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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.
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This course on Integrate Vertex AI Search and Conversation into Voice and Chat Apps is composed of a set of labs to give you a hands on experience to interacting with new Generative AI technologies. You will learn how to create end-to-end search and conversational experiences by following examples. These technologies complement predefined intent-based chat experiences created in Dialogflow with LLM-based, generative answers that can be based on your own data. Also, they allow you to porvide enterprise-grade search experiences for internal and external websites to search documents, structure data and public websites.
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在本新手级课程中，您将了解 Google Cloud 数据分析工作流，以及可用于探索、分析和直观呈现数据并与相关人员共享发现结果的工具。结合案例研究、实操实验、讲座和测验/演示，本课程展示了如何将原始数据集转化为纯净数据，进而转化为实用的可视化图表和信息中心。无论您是已经在从事数据工作并想了解如何通过 Google Cloud 取得成功，还是在寻求职业发展，都可以借助本课程迈出第一步。几乎所有在工作中执行或使用数据分析的人都可以从本课程中受益。
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This course is designed for data analysts who want to learn about using BigQuery for their data analysis needs. Through a combination of videos, labs, and demos, we cover various topics that discuss how to ingest, transform, and query your data in BigQuery to derive insights that can help in business decision making.
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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
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This learning path aims to upskill Google Cloud partners to perform the specific tasks associated with the priority workload. Learners will discover the specific tasks in rehosting applications from on-premises to Google Cloud. It also aims to re-platform applications to run in GKE. Learners will perform the tasks of Migrating MySQL, Angular, and .NET applications from their on-premises machines to Google Cloud VM instances. Sample code will be used during the migration. Learners will complete a challenge lab that focuses on the critical steps in a rehosting exercise - copying over code for the back-end, front-end, and middle-tier applications and validating that the applications have been migrated correctly. Learners will also complete a challenge lab that focuses on the critical steps in a re-platforming exercise - creating back-end, front-end, and middle-tier Docker images, deploying the same in the GKE cluster, and validating that the application has been deployed correctly.
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As organizations move their data and applications to the cloud, they must address new security challenges. The Trust and Security with Google Cloud course explores the basics of cloud security, the value of Google Cloud's multilayered approach to infrastructure security, and how Google earns and maintains customer trust in the cloud.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Get hands-on practice with Google Cloud! You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points.
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This challenge lab tests your skills and knowledge from the labs in the Monitor and Manage Google Cloud Resources quest. You should be familiar with the content of labs before attempting this lab.
Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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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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Earn a DRI badge by completing the Smart Analytics - Implementing Dataplex quest, where you demonstrate your proficiency of implementing Dataplex foundations, security, tagging, data curation and data quality.
When you complete this activity, you can earn the badge displayed above! View all the badges you have earned by visiting your profile page.
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完成入门技能徽章课程使用 Dataplex 构建数据网格，展示以下方面的技能：使用 Dataplex 构建数据网格， 以在 Google Cloud 上实现数据安全、治理和发现。您将在 Dataplex 中练习和测试自己在标记资产、分配 IAM 角色和评估数据质量方面的技能。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛，即可获得数字徽章， 在您的人际圈中炫出自己的技能。
In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate managed services from Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants learn how to apply best practices for application development and use the appropriate Google Cloud storage services for object storage, relational data, caching, and analytics.
Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer.
This is the first course of the Developing Applications with Google Cloud series. After completing this course, enroll in the Securing and Integrating Components of your Application course.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
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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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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）如何帮助工程师管理基础设施。您将了解如何向 Gemini 输入提示，让其查找和理解应用日志、创建 GKE 集群，以及研究如何创建构建环境。您可以通过实操实验了解如何利用 Gemini 来改进 DevOps 工作流。
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）如何帮助网络工程师创建、更新和维护 VPC 网络。您将学习如何向 Gemini 输入提示，让其针对您的网络组建和管理任务，提供您从搜索引擎所无法获得的具体指导。您可以通过实操实验了解如何利用 Gemini 更轻松地使用 Google Cloud VPC 网络。
Duet AI 已更名为 Gemini，这是我们的新一代模型。
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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps.
We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views.
After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.
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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 Dataproc 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。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可您在 Google Cloud 产品与服务方面的熟练度； 您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得技能徽章，在您的人际圈中炫出自己的技能。
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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。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您对 Google Cloud 产品与服务的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成技能徽章课程和 作为最终评估的实验室挑战赛，即可获得数字徽章， 在您的人际圈中炫出自己的技能。
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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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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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Google Workspace 专用 Gemini 是一个插件，可在 Google Workspace 中为客户提供生成式 AI 功能。在本迷你课程中，您将了解 Gemini 的主要功能，以及如何在 Google 幻灯片中使用它们来提高工作效率。
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在本课程中，您将了解 Google Cloud 中依托生成式 AI 技术的协作工具 Gemini 如何帮助开发者构建应用。您将学习如何向 Gemini 输入提示，让其为您解释代码、推荐 Google Cloud 服务并为您的应用生成代码。您将通过实操实验体验 Gemini 对应用开发工作流的改进作用。
Duet AI 已更名为 Gemini，这是我们的新一代模型。
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Google Workspace 专用 Gemini 是一个插件，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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Google Workspace 专用 Gemini 是一个插件，可在 Google Workspace 中为客户提供生成式 AI 功能。在本迷你课程中，您将了解 Gemini 的主要功能，以及如何在 Gmail 中使用这些功能来提高工作效率。
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Google Workspace 专用 Gemini 是一个插件，用户可通过它来使用生成式 AI 功能。本课程通过视频课程、实操活动和实际示例，深入探讨了“Google 文档中的 Gemini”的功能。您将学习如何使用 Gemini 来根据提示生成书面内容。您还会探索如何使用 Gemini 来修改已撰写好的文本，帮助提升整体工作效率。学完本课程后，您将掌握相关知识和技能，能够自信地利用 Google 文档中的 Gemini 来提升写作水平。
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Google Workspace 专用 Gemini 是一个插件，可在 Google Workspace 中为客户提供生成式 AI 功能。在本迷你课程中，您将了解 Gemini 的主要功能，以及如何在 Google 表格中使用它们来提高工作效率。
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在本课程中，您将了解 Gemini（Google Cloud 的生成式 AI 赋能的协作工具）如何帮助管理员预配基础设施。您将了解如何通过输入提示来让 Gemini 解释基础设施、GKE 集群的部署，以及现有基础设施的更新。您可以通过实操实验了解如何利用 Gemini 来改进 GKE 部署工作流。
Duet AI 已更名为 Gemini，这是我们的新一代模型。
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完成中级技能徽章课程使用 BigQuery 构建数据仓库，展示以下技能： 联接数据以创建新表、排查联接故障、使用并集附加数据、创建日期分区表， 以及在 BigQuery 中使用 JSON、数组和结构体。 技能徽章是 Google Cloud 颁发的专属数字徽章， 旨在认可您在 Google Cloud 产品与服务方面的熟练度； 您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后 才能获得。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得数字徽章，在您的人际圈中炫出自己的技能。
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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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Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
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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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这是一节入门级微课程，旨在解释什么是负责任的 AI、它的重要性，以及 Google 如何在自己的产品中实现负责任的 AI。此外，本课程还介绍了 Google 的 7 个 AI 开发原则。
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The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud 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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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.
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完成在 Vertex AI 上构建和部署机器学习解决方案课程，赢取中级技能徽章。 在此课程中，您将了解如何使用 Google Cloud 的 Vertex AI Platform、AutoML 以及自定义训练服务来 训练、评估、调优、解释和部署机器学习模型。 此技能徽章课程的目标受众是专业的数据科学家和机器学习 工程师。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您对 Google Cloud 产品与服务的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能徽章课程 和作为最终评估的实验室挑战赛，即可获得数字徽章， 在您的人际圈中炫出自己的技能。
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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。 技能徽章是 由 Google Cloud 颁发的专有数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在交互式实操环境中参加考核， 证明自己运用所学知识的能力后才能获得。完成此技能徽章课程和 作为最终评估的实验室挑战赛，即可获得技能徽章，并在您的社区圈中秀一秀 自己的水平。
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Good news! There’s a new updated version of this learning path available for you!Open the new Professional Cloud DevOps Engineer Certification Learning Path to begin, once you’ve selected the new path all your current progress will be reflected in the new version.
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完成入门级使用 Google Cloud Observability 进行监控和记录技能徽章课程， 展示自己在以下方面的技能：监控 Compute Engine 中的虚拟机； 利用 Cloud Monitoring 监控多个项目；将监控和日志记录功能扩展到 Cloud Functions； 创建和发送自定义应用指标；以及根据自定义指标配置 Cloud Monitoring 提醒。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能 徽章课程和作为最终评估的实验室挑战赛，获得技能徽章， 在您的人际圈中炫出自己的技能。
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完成在 Google Cloud 中实施 DevOps 工作流技能徽章中级课程， 展示您在以下方面的技能：利用 Cloud Source Repositories 创建 git 代码库； 在 Google Kubernetes Engine (GKE) 上启动、管理和扩缩 Deployment； 设计 CI/CD 流水线架构，以自动构建容器映像并将其部署到 GKE。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能 徽章课程和作为最终评估的实验室挑战赛，获得技能徽章， 在您的人际圈中炫出自己的技能。
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Course two of the Architecting Hybrid Cloud with Anthos series prepares students to operate and observe Anthos environments. Through presentations and hands-on labs, participants explore adjusting existing clusters, setting up advanced traffic routing policies, securing communication across workloads, and observing clusters in Anthos. This course is a continuation of course one, Multi-Cluster, Multi-Cloud with Anthos, and assumes direct experience with the topics covered in that course.
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本课程指导学员运用久经考验的设计模式在 Google Cloud 上构建高度可靠且高效的解决方案。它是“Google Compute Engine 架构设计”或“Google Kubernetes Engine 架构设计”课程的延续，并假定您有使用其中任何一门课程所涵盖技术的实践经验。通过一系列演示、设计活动和动手实验，学员可以了解如何定义及平衡业务要求和技术要求，以便设计可靠性和可用性高、安全且经济实惠的 Google Cloud 部署。
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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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This course teaches participants techniques for monitoring and improving infrastructure and application performance in Google Cloud.
Using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage.
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完成入门级技能徽章课程“从 BigQuery 数据中挖掘数据洞见”，展示您在以下方面的技能： 编写 SQL 查询、查询公共表、将示例数据加载到 BigQuery 中、 在 BigQuery 中使用查询验证器排查常见的语法错误，以及通过连接到 BigQuery 数据在 Looker Studio 中 创建报告。 技能徽章是由 Google Cloud 颁发的专属数字徽章， 旨在认可您在 Google Cloud 产品与服务方面的熟练度。 您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章 。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得技能徽章，在您的人际圈中炫出自己的技能。
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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
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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。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛，即可获得技能徽章， 在您的人际圈中炫出自己的技能。
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完成为 Looker 信息中心和报告准备数据入门级技能徽章课程， 展现您在以下方面的技能：对数据进行过滤、排序和透视；将来自不同 Looker 探索的结果合并； 以及使用函数和运算符构建 Looker 信息中心和报告以用于数据分析和可视化。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在交互式实操环境中参加考核， 证明自己运用所学知识的能力后才能获得此徽章。完成此技能徽章课程和 作为最终评估的实验室挑战赛，即可获得技能徽章，在您的人际圈中 炫出自己的技能。
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In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.
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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This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure.
Learners will get hands-on practice building and managing Google Cloud resources using Terraform.
在此入门级挑战任务中，您可以使用 Google Cloud Platform 的基本工具和服务，开展真枪实弹的操作实训。“GCP 基本功能”是我们为 Google Cloud 学员推荐的第一项挑战任务。云知识储备微乎其微甚至零基础？不用担心！这项挑战任务会为您提供真枪实弹的实操经验，助您快速上手 GCP 项目。无论是要编写 Cloud Shell 命令还是部署您的第一台虚拟机，亦或是通过负载平衡机制或在 Kubernetes Engine 上运行应用，都可以通过“GCP 基本功能”了解该平台的基本功能之精要。点此观看 1 分钟视频，了解每个实验涉及的主要概念。
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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。 技能徽章是由 Google Cloud 颁发的专属数字徽章， 旨在认可您在 Google Cloud 产品与服务方面的熟练度；您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能徽章课程和作为最终评估的实验室挑战赛，获得技能徽章，在您的人际圈中炫出自己的技能。
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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task.
Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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欢迎学习“Google Kubernetes Engine 使用入门”课程。Kubernetes 是位于应用和硬件基础架构之间的软件层，如果您对 Kubernetes 感兴趣，那就来对地方了！Google Kubernetes Engine 将 Kubernetes 作为 Google Cloud 上的代管式服务提供给您使用。
本课程的目标是介绍 Google Kubernetes Engine（通常称为 GKE）的基础知识，以及将应用容器化并在 Google Cloud 中运行的方法。本课程首先介绍 Google Cloud 的基础知识，然后概述容器、Kubernetes、Kubernetes 架构以及 Kubernetes 操作。
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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences.
“Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.
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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. "Modernize Infrastructure and Applications with Google Cloud" explores these challenges and offers solutions to overcome them by using cloud technology.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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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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There's much excitement about cloud technology and digital transformation, but often many unanswered questions.
For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin?
If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.
Google Workspace Troubleshooting
Earned Sep 15, 2025 EDT
使用 Vertex AI 和 Flutter 构建生成式 AI 智能体
Earned Aug 25, 2025 EDT
Integrate BigQuery Data and Google Workspace using Apps Script
Earned Aug 20, 2025 EDT
Evaluate Gen AI model and agent performance
Earned Aug 1, 2025 EDT
Evaluate ADK Agents with Vertex AI Gen AI Evaluation Service
Earned Aug 1, 2025 EDT
Implement Hybrid Search
Earned Aug 1, 2025 EDT
Implement RAG with Vertex AI
Earned Aug 1, 2025 EDT
使用 BigQuery 创建嵌入、向量搜索和 RAG
Earned Aug 1, 2025 EDT
Deploy a RAG application with vector search in Firestore
Earned Aug 1, 2025 EDT
Edit images with Imagen
Earned Aug 1, 2025 EDT
Build Gen AI solutions using Model Garden models and APIs
Earned Jul 31, 2025 EDT
Find, Explore and Deploy Model Garden Models
Earned Jul 31, 2025 EDT
Improve Performance by Fine-Tuning Foundation Models
Earned Jul 31, 2025 EDT
利用 Vertex AI 实现机器学习运维 (MLOps)：模型评估
Earned Jul 31, 2025 EDT
Generate and Edit Media with Imagen, Gemini, and Veo
Earned Jul 31, 2025 EDT
Empower Gen AI apps with tool use
Earned Jul 30, 2025 EDT
Engineer Effective Prompts for Generative Models
Earned Jul 30, 2025 EDT
Explore Google's Gen AI Models
Earned Jul 30, 2025 EDT
Extend Gemini with controlled generation and Tool use
Earned Jul 30, 2025 EDT
Create media search and media recommendations applications with AI Applications
Earned Jul 30, 2025 EDT
Configure AI Applications to optimize search results
Earned Jul 30, 2025 EDT
Recommendations with AI Applications
Earned Jul 29, 2025 EDT
Extend Google Agentspace assistant capabilities
Earned Jul 29, 2025 EDT
Introduction to NotebookLM
Earned Jul 29, 2025 EDT
Vertex AI Search and Google Agentspace Analytics
Earned Jul 29, 2025 EDT
Vertex AI Search and Google Agentspace UI Configurations
Earned Jul 29, 2025 EDT
Create and maintain Vertex AI Search data stores
Earned Jul 29, 2025 EDT
Improve Vertex AI Search and Google Agentspace Search Results
Earned Jul 29, 2025 EDT
Create Data Stores for Gen AI Applications
Earned Jul 29, 2025 EDT
Introduction to AI Applications
Earned Jul 29, 2025 EDT
Build search and recommendations applications with AI Applications
Earned Jul 28, 2025 EDT
Leverage best practices for developing, operating, and securing production-grade Conversational Agents
Earned Jul 28, 2025 EDT
Build Production-Ready Conversational Agents
Earned Jul 28, 2025 EDT
Customer Engagement Suite with Google AI Architecture
Earned Jul 28, 2025 EDT
Advanced Performance Measurement
Earned Jul 25, 2025 EDT
Basic Performance Measurement
Earned Jul 25, 2025 EDT
Agent Summarization (Custom)
Earned Jul 25, 2025 EDT
Integrate Agent Assist with Telephony and Chatbot Systems
Earned Jul 25, 2025 EDT
Conversational Insights
Earned Jul 25, 2025 EDT
Analyze patterns in conversational data with Conversational Insights
Earned Jul 25, 2025 EDT
Introduction to Agent Assist and its GenAI Capabilities
Earned Jul 25, 2025 EDT
Improve customer and agent satisfaction with Agent Assist
Earned Jul 25, 2025 EDT
Conversational AI Voice and Chat Integrations
Earned Jul 25, 2025 EDT
Extend virtual agents with webhooks, tools, and Messenger integration
Earned Jul 25, 2025 EDT
Extend Conversational Agents Functionality with Webhooks and Tools
Earned Jul 25, 2025 EDT
Virtual FAQ with data store agents
Earned Jul 24, 2025 EDT
Incorporate Generative Features into Conversational Agent flows
Earned Jul 24, 2025 EDT
Stateful Flows
Earned Jul 24, 2025 EDT
Generative Playbooks
Earned Jul 24, 2025 EDT
Introduction to CES and Conversational Agents
Earned Jul 24, 2025 EDT
Build basic Conversational Agents with Playbooks and Flows
Earned Jul 18, 2025 EDT
面向开发者的 Responsible AI：隐私保护和安全
Earned Jun 13, 2025 EDT
面向开发者的 Responsible AI：可解释性和透明度
Earned Jun 12, 2025 EDT
适用于生成式 AI 的机器学习运维 (MLOps)
Earned Jun 12, 2025 EDT
创建图片标注模型
Earned Jun 12, 2025 EDT
Transformer 模型和 BERT 模型
Earned Jun 12, 2025 EDT
编码器-解码器架构
Earned Jun 11, 2025 EDT
注意力机制
Earned Jun 11, 2025 EDT
图像生成简介
Earned Jun 11, 2025 EDT
大型语言模型简介
Earned Jun 11, 2025 EDT
生成式 AI 简介
Earned Jun 11, 2025 EDT
Google Workspace Data Governance
Earned Jun 11, 2025 EDT
Gen AI Agents: Transform Your Organization
Earned Jun 10, 2025 EDT
Gen AI: Navigate the Landscape
Earned Jun 9, 2025 EDT
Gen AI: Beyond the Chatbot
Earned Jun 3, 2025 EDT
Gen AI Apps: Transform Your Work
Earned Jun 3, 2025 EDT
Google Workspace Core Services
Earned May 30, 2025 EDT
借助 Agentspace 加速知识交流
Earned May 29, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned May 29, 2025 EDT
Build LookML Objects in Looker
Earned Apr 18, 2025 EDT
Understanding LookML in Looker
Earned Apr 18, 2025 EDT
Data Warehousing for Partners: Analyze Data with Looker
Earned Apr 18, 2025 EDT
Analyzing and Visualizing Data in Looker
Earned Apr 15, 2025 EDT
在 Google Cloud 上实施云安全基础措施
Earned Mar 13, 2025 EDT
Google Cloud 数据工程简介
Earned Mar 5, 2025 EST
基准：基础架构
Earned Mar 5, 2025 EST
矢量搜索和嵌入
Earned Nov 7, 2024 EST
Get Started with Eventarc
Earned Nov 6, 2024 EST
Cloud Run Functions: 3 Ways
Earned Nov 6, 2024 EST
Create a Streaming Data Lake on Cloud Storage
Earned Oct 24, 2024 EDT
在 Cloud Storage 上创建安全的数据湖
Earned Oct 24, 2024 EDT
Monitoring in Google Cloud
Earned Oct 24, 2024 EDT
使用 Vertex AI 中的 Gemini API 探索生成式 AI
Earned Oct 23, 2024 EDT
在 Google Cloud 上存储、处理和管理数据 - 控制台
Earned Oct 22, 2024 EDT
Use APIs to Work with Cloud Storage
Earned Oct 22, 2024 EDT
Google Cloud 云计算基础知识
Earned Oct 22, 2024 EDT
Tag and Discover BigLake Data
Earned Oct 21, 2024 EDT
BigQuery 流式数据分析
Earned Oct 21, 2024 EDT
Secure BigLake Data
Earned Oct 21, 2024 EDT
Automate Data Migrations to BigQuery
Earned Oct 18, 2024 EDT
Get Started with Cloud Storage
Earned Oct 18, 2024 EDT
Pub/Sub 使用入门
Earned Oct 16, 2024 EDT
API Gateway 使用入门
Earned Oct 15, 2024 EDT
Google Workspace User and Resource Management
Earned Aug 8, 2024 EDT
DEPRECATED Planning for a Google Workspace Deployment
Earned Aug 7, 2024 EDT
Google Workspace Security
Earned Aug 6, 2024 EDT
Configure your Workplace: Google Workspace for IT Admins
Earned Aug 5, 2024 EDT
在 Vertex AI 中设计提示
Earned Jul 24, 2024 EDT
Generative AI Fundamentals
Earned Jul 22, 2024 EDT
Vertex AI Studio 简介
Earned Jul 22, 2024 EDT
Google Cloud 上的 AI 和机器学习简介
Earned Jul 22, 2024 EDT
构建安全的 Google Cloud 网络
Earned Jul 19, 2024 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned Jul 19, 2024 EDT
Google Cloud Computing Foundations: Networking & Security in Google Cloud
Earned Jul 19, 2024 EDT
Google Cloud Computing Foundations: Cloud Computing Fundamentals
Earned Jul 18, 2024 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned Jul 18, 2024 EDT
Generative AI for Business Leaders
Earned Jul 17, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Jul 17, 2024 EDT
Google Cloud 数据分析功能简介
Earned Jul 17, 2024 EDT
BigQuery for Data Analysts
Earned Jul 16, 2024 EDT
Text Prompt Engineering Techniques
Earned Jul 12, 2024 EDT
.NET Modernization
Earned May 28, 2024 EDT
Trust and Security with Google Cloud
Earned May 28, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned May 28, 2024 EDT
Cloud Hero Infra II Skills
Earned May 27, 2024 EDT
Monitor and Manage Google Cloud Resources
Earned May 20, 2024 EDT
在 Compute Engine 上实现负载均衡
Earned May 13, 2024 EDT
在 Google Cloud 上部署 Kubernetes 应用
Earned Apr 26, 2024 EDT
Architecting with Google Kubernetes Engine: Foundations - 简体中文
Earned Apr 26, 2024 EDT
DEPRECATED BigQuery for Data Warehousing
Earned Feb 16, 2024 EST
Preparing for your Professional Cloud Architect Journey
Earned Feb 15, 2024 EST
Smart Analytics - Implementing Dataplex
Earned Feb 15, 2024 EST
使用 Dataplex 构建数据网格
Earned Feb 2, 2024 EST
Dataplex 使用入门
Earned Jan 30, 2024 EST
Getting Started With Application Development
Earned Jan 19, 2024 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud
Earned Jan 17, 2024 EST
适用于端到端 SDLC 的 Gemini
Earned Jan 15, 2024 EST
适用于 DevOps 工程师的 Gemini
Earned Jan 15, 2024 EST
适用于网络工程师的 Gemini
Earned Jan 15, 2024 EST
Achieving Advanced Insights with BigQuery
Earned Jan 15, 2024 EST
在 Google Cloud 上为机器学习 API 准备数据
Earned Jan 11, 2024 EST
利用 BigQuery ML 构建预测模型时的数据工程处理
Earned Jan 10, 2024 EST
面向数据科学家和分析师的 Gemini
Earned Jan 10, 2024 EST
适用于安全工程师的 Gemini
Earned Jan 10, 2024 EST
Google 幻灯片中的 Gemini
Earned Jan 8, 2024 EST
适用于应用开发者的 Gemini
Earned Jan 8, 2024 EST
Gemini for Google Workspace 简介
Earned Jan 8, 2024 EST
Gmail 中的 Gemini
Earned Jan 8, 2024 EST
Google 文档中的 Gemini
Earned Jan 8, 2024 EST
Google 表格中的 Gemini
Earned Jan 8, 2024 EST
适用于云架构师的 Gemini
Earned Jan 8, 2024 EST
使用 BigQuery 构建数据仓库
Earned Jan 5, 2024 EST
Serverless Data Processing with Dataflow: Foundations
Earned Jan 4, 2024 EST
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Jan 3, 2024 EST
Building Batch Data Pipelines on Google Cloud
Earned Dec 18, 2023 EST
Responsible AI: 和 Google Cloud 一起践行 AI 原则
Earned Dec 14, 2023 EST
负责任的 AI 简介
Earned Dec 13, 2023 EST
Modernizing Data Lakes and Data Warehouses with Google Cloud
Earned Dec 12, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Nov 8, 2023 EST
Preparing for your Professional Data Engineer Journey
Earned Sep 29, 2023 EDT
在 Vertex AI 上构建和部署机器学习解决方案
Earned Jun 15, 2023 EDT
开发 Google Cloud 网络
Earned Jun 1, 2023 EDT
Certification Learning Path: Professional Cloud DevOps Engineer
Earned May 30, 2023 EDT
使用 Google Cloud Observability 进行监控和记录
Earned May 29, 2023 EDT
在 Google Cloud 中实施 DevOps 工作流
Earned May 26, 2023 EDT
DEPRECATED Cloud Operations and Service Mesh with Anthos
Earned May 25, 2023 EDT
可靠的 Google Cloud 基础设施: 设计和流程
Earned May 24, 2023 EDT
Developing a Google SRE Culture
Earned May 19, 2023 EDT
Logging and Monitoring in Google Cloud
Earned May 18, 2023 EDT
从 BigQuery 数据中挖掘数据洞见
Earned Feb 9, 2023 EST
Launching into Machine Learning
Earned Feb 9, 2023 EST
通过 BigQuery ML 创建机器学习模型
Earned Jan 27, 2023 EST
为 Looker 信息中心和报告准备数据
Earned Jan 27, 2023 EST
Applying Machine Learning to your Data with Google Cloud
Earned Jan 26, 2023 EST
面向机器学习的 BigQuery
Earned Jan 25, 2023 EST
Google Cloud 重要基础设施：核心服务
Earned Nov 22, 2022 EST
Getting Started with Terraform for Google Cloud
Earned Nov 21, 2022 EST
在 Google Cloud 上使用 Terraform 构建基础设施
Earned Oct 4, 2022 EDT
在 Compute Engine 上实现负载均衡
Earned Oct 3, 2022 EDT
Google Cloud Essentials
Earned Oct 3, 2022 EDT
在 Google Cloud 上设置应用开发环境
Earned Aug 5, 2022 EDT
Scaling with Google Cloud Operations
Earned Aug 4, 2022 EDT
Google Kubernetes Engine 使用入门
Earned Aug 4, 2022 EDT
Exploring Data Transformation with Google Cloud
Earned Jul 25, 2022 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned Jul 25, 2022 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned Jul 20, 2022 EDT
Google Cloud 基础知识：核心基础设施
Earned Jul 19, 2022 EDT
Digital Transformation with Google Cloud
Earned Jul 11, 2022 EDT