Introduction to Generative AI - 简体中文
Earned Jul 5, 2023 EDT
Vertex AI Studio 简介
Earned Jul 5, 2023 EDT
Generative AI Fundamentals - 简体中文
Earned Jul 5, 2023 EDT
生成式 AI 简介
Earned Jul 4, 2023 EDT
图像生成简介
Earned Jul 3, 2023 EDT
创建图片标注模型
Earned Jul 3, 2023 EDT
编码器-解码器架构
Earned Jul 3, 2023 EDT
探索生成式 AI - Vertex AI
Earned Jul 3, 2023 EDT
Techcon 2023 Industry Game
Earned May 18, 2023 EDT
Techcon 2023 Platform Game
Earned May 17, 2023 EDT
Techcon 2023 Data & AI Game
Earned May 16, 2023 EDT
使用 Google Cloud Managed Service for Prometheus 来监控环境
Earned Mar 24, 2023 EDT
通过 BigQuery ML 创建机器学习模型
Earned Mar 12, 2023 EDT
在 Vertex AI 上构建和部署机器学习解决方案
Earned Mar 10, 2023 EST
借助 Firebase 开发无服务器应用
Earned Feb 13, 2023 EST
在 Google Cloud 上实施云安全基础措施
Earned Feb 11, 2023 EST
在 Cloud Run 上开发无服务器应用
Earned Feb 9, 2023 EST
为 Compute Engine 实现云负载均衡
Earned Feb 7, 2023 EST
在 Google Cloud 上部署 Kubernetes 应用
Earned Feb 7, 2023 EST
从 BigQuery 数据中挖掘数据洞见
Earned Feb 4, 2023 EST
使用 BigQuery 构建数据仓库
Earned Feb 1, 2023 EST
DEPRECATED Detect Manufacturing Defects Using Visual Inspection AI
Earned Jan 28, 2023 EST
用 Document AI 实现大规模自动数据采集
Earned Jan 27, 2023 EST
在 Google Cloud 上设置应用开发环境
Earned Jan 25, 2023 EST
开发 Google Cloud 网络
Earned Jan 20, 2023 EST
在 Google Cloud 上使用 Terraform 构建基础设施
Earned Jan 19, 2023 EST
创建和管理 Cloud Spanner 实例
Earned Jan 17, 2023 EST
用 Google Data Cloud 共享数据
Earned Dec 28, 2022 EST
Managing Cloud Infrastructure with Terraform
Earned Dec 25, 2022 EST
云架构：设计、实施和管理
Earned Dec 24, 2022 EST
利用 BigQuery ML 构建预测模型时的数据工程处理
Earned Dec 24, 2022 EST
为 Looker 信息中心和报告准备数据
Earned Dec 23, 2022 EST
在 Google Cloud 上使用 Machine Learning API
Earned Dec 21, 2022 EST
Migrating MySQL data to Cloud SQL using Database Migration Service
Earned Dec 8, 2022 EST
DEPRECATED Cloud Architecture
Earned Aug 27, 2022 EDT
In this course, you'll learn to develop AI agents that answer questions using websites, documents, or structured data. You will explore 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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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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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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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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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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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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“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: 全面了解生成式 AI”是 Generative 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,以及我们与周围世界的互动方式。作为领导者,应该如何利用生成式 AI 来推动实现实际的业务成果?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,以及选择解决方案时需要考虑的因素。
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“生成式 AI: 剖析基本概念”是 Generative AI Leader 学习路线中的第二门课程。在本课程中,您将了解生成式 AI 的基本概念。您要探索 AI、机器学习和生成式 AI 之间的区别,了解各种数据类型如何赋能生成式 AI,从而应对各种业务挑战。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 开发与部署面临着哪些关键挑战。
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“生成式 AI：不只是聊天机器人”是 Generative AI Leader 学习路线中的第一门课程。学习本课程没有知识门槛。本课程旨在帮助您超越对聊天机器人的基本认知,探索生成式 AI技术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,这些知识对利用生成式 AI 的强大功能至关重要。本课程还将说明,为组织制定成功的生成式 AI 策略时,需要考虑哪些重要因素。
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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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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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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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Explore a variety of techniques for using Gemini to understand image, audio, video, and live-streaming media. You will discover how meaningful information can be extracted from each of these forms of media to use in media-rich applications.
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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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This course will focus on Agent Assist, an AI-powered tool designed to enhance customer service interactions. In this course, you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the chat channel. You’ll learn how to take full advantage of Agent Assist from Gemini Enterprise for Customer Experience, and its range of Gen AI features and functionality.
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This course dives into the world of media creation in Vertex AI using Nano Banana and Veo. Learn to design text and image-based prompts to produce high-quality, consistent images, and captivating, cinematic video clips. You'll also learn to refine generated assets using core editing functions. Finally, this course guides you through multi-tool workflow implementations for creative control and consistency, empowering you to transform images into video clips and leverage Gemini for prompt writing assistance and feedback.
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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. You will also learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents.
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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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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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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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In this skill bagde, you will demonstrate your ability to use and compare models available in the Vertex AI Model Garden. You'll deploy a model to a Vertex AI Endpoint, query other models via their API, and use Vertex AI's Gen AI evaluation service to measure the performance of multiple models.
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With this course you will learn how to use different techniques to fine-tune Gemini. Model tuning is an effective way to customize large models like Gemini for your specific tasks. It's a key step to improve the model's quality and efficiency.
This course will give an overview of model tuning, describe the tuning options available for Gemini, help you determine when each tuning option should be used and how to perform tuning.
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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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This course delves into the complexities of assessing the quality of large language model outputs. It examines the challenges enterprises face due to the subjective and sometimes incorrect nature of LLM responses, including hallucinations and inconsistent results. The course introduces various evaluation metrics for different tasks like classification, text generation, and question answering, such as Accuracy, Precision, Recall, F1 score, ROUGE, BLEU, and Exact Match. It also explores evaluation methods offered by Vertex AI LLM Evaluation Services, including computation-based, autorater, and human evaluation, providing insights into their application and benefits. Finally, the module covers how to unit test LLM applications within Vertex AI.
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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 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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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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Complete the Analyze patterns in conversational data with Customer Experience Insights skill badge to demonstrate your proficiency in analysing customer conversations with Cx Insights. After completing this challenge, you will be ready to deploy Cx 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 to leverage Customer Experience Insights (CX Insights) to uncover hidden information from your contact center data to increase operational efficiency and drive data-driven business decisions.
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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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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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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.
(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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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.
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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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This course explores the different products and capabilities of Gemini Enterprise for Customer Experience 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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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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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 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!
了解详情
AI Applications provides built-in analytics for your Vertex AI Search and Gemini Enterprise apps. Learn what metrics are tracked and how to view them in this course.
(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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Initial deployment of Vertex AI 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.
(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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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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In this skill badge, you will demonstrate your ability to deploy Google Agentspace and set up data stores and actions. To learn these skills, we encourage you to take the course Accelerate Knowledge Exchange with Agentspace.
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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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In this course, you will learn the important role that different types of webhooks play in Conversational Agents development, and how to effectively integrate them into your routine configuration of a Conversational Agent. 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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This course explores advanced technical considerations to optimize Webhook connectivity for comprehensive, end-to-end, Conversational Agent self-service experiences. 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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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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(Previously named "Developing apps with Vertex AI Agent Builder: Search". Please note there maybe instances in this course where previous product names and titles are used)
Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use AI Applications to integrate enterprise-grade generative AI search.
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Welcome to the TechCon2023 Industry Solutions Labs & Quizzes!
You can find all of our technical learning packs on go/techlearningpacks and industry learning packs on go/industrylearningpacks.
Subscribe to Learning Pack updates for latest content and metrics on go/enablementannouncements-alltrainings.
Brought to you by the CLS Tech Specialization Team (cce-enablement-tech@). Share your request/feedback on go/learningpacks-feedback!
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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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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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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完成 Introduction to Generative AI、Introduction to Large Language Models 和 Introduction to Responsible AI 三门课程，赢取技能徽章。通过最终测验，即表明您理解了生成式 AI 的基本概念。
技能徽章是由 Google Cloud 颁发的数字徽章，旨在认可您对 Google Cloud 产品与服务的了解程度。公开您的个人资料并将技能徽章添加到您的社交媒体个人资料中，以此来分享您获得的成就。
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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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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。
探索生成式 AI - Vertex AI 课程汇集了多组实验， 指导用户在 Google Cloud 平台上运用生成式 AI。参与实验，您将了解 如何使用 Vertex AI PaLM API 系列模型，包括 text-bison、chat-bison 和 textembedding-gecko。您还将了解提示设计、最佳实践， 以及如何使用生成式 AI 进行构思、文本分类、文本提取、文本 总结等任务。您还将学习如何通过 Vertex AI 自定义训练对基础模型进行调优， 并将模型部署到 Vertex AI 端点。
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Welcome to the TechCon2023 Industry Solutions Game!
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Welcome to the TechCon 2023 Platform Game!!
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Welcome to the TechCon2023 Data & AI Game!
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完成使用 Google Cloud Managed Service for Prometheus 来监控环境这一技能徽章课程，赢取技能徽章。在此课程中，您将学习如何使用 Google Cloud Managed Service for Prometheus 监控 Kubernetes。
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完成中级技能徽章课程通过 BigQuery ML 创建机器学习模型，展示您在以下方面的技能： 使用 BigQuery ML 创建和评估机器学习模型，以执行数据预测。
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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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完成借助 Firebase 开发无服务器应用技能徽章中级课程， 展示您在以下方面的技能：借助 Firebase 设计无服务器 Web 应用架构以及构建无服务器 Web 应用； 利用 Firestore 管理数据库；利用 Cloud Build 自动完成部署流程； 以及将 Google 助理功能集成到您的应用中。
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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。
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完成在 Cloud Run 上开发无服务器应用技能徽章中级课程， 展示您在以下方面的技能：集成 Cloud Run 与 Cloud Storage 以管理数据， 使用 Cloud Run 和 Pub/Sub 设计弹性异步系统架构， 构建依托 Cloud Run 技术的 REST API 网关，以及在 Cloud Run 上构建和部署服务。
Earn a skill badge by completing the Detect Manufacturing Defects using Visual Inspection AI course, where you learn how to use Visual Inspection AI to deploy a solution artifact and test that it can successfully identify defects in a manufacturing process.
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完成用 Document AI 实现大规模自动数据采集课程，赢取入门级技能徽章。在本课程中，您将学习如何使用 Document AI 提取、处理和采集数据。
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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。
完成用 Google Data Cloud 共享数据技能徽章课程，赢取技能 徽章。您将获得使用 Google Cloud 数据共享合作伙伴 的实操经验，这些合作伙伴拥有专有数据集， 客户可将其用于自己的分析应用场景。客户订阅这些数据集，可在自己的 平台上查询，然后使用自己的数据集加以扩充，并使用自己的可视化 工具，用于面向客户的信息中心。
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In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.
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完成 云架构：设计、实施和管理课程，赢取技能徽章，展示您在以下方面的技能：使用 Apache Web 服务器部署可公开访问的网站；使用启动脚本配置 Compute Engine 虚拟机； 使用 Windows 堡垒主机和防火墙规则配置安全 RDP；构建 Docker 映像并将其部署到 Kubernetes 集群，然后进行更新；以及创建 CloudSQL 实例并导入 MySQL 数据库。 此技能徽章课程是非常有用的资源， 可帮助您理解 Google Cloud 认证 Professional Cloud Architect 认证考试中将会出现的主题。
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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。
完成在 Google Cloud 上使用 Machine Learning API 课程，赢取高级技能徽章。 在本课程中，您将了解以下机器学习和 AI 技术的基本功能： Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。
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This course offers hands-on practice with migrating MySQL data to Cloud SQL using Database Migration Service. You start with an introductory lab that briefly reviews how to get started with Cloud SQL for MySQL, including how to connect to Cloud SQL instances using the Cloud Console. Then, you continue with two labs focused on migrating MySQL databases to Cloud SQL using different job types and connectivity options available in Database Migration Service. The course ends with a lab on migrating MySQL user data when running Database Migration Service jobs.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
Extend CX Agents with Vertex AI Search data stores
Earned Nov 22, 2025 EST
Build basic Conversational Agents with Playbooks and Flows
Earned Nov 21, 2025 EST
Extend virtual agents with webhooks, tools, and Messenger integration
Earned Nov 21, 2025 EST
Improve customer and agent satisfaction with Agent Assist
Earned Nov 20, 2025 EST
Empower Gen AI Apps with Tool Use
Earned Nov 20, 2025 EST
Extend Gemini with controlled generation and Tool use
Earned Nov 20, 2025 EST
生成式 AI 智能体：助力组织转型
Earned Nov 14, 2025 EST
生成式 AI 应用：改变工作方式
Earned Nov 14, 2025 EST
生成式 AI: 全面了解生成式 AI
Earned Nov 14, 2025 EST
生成式 AI：剖析基本概念
Earned Nov 14, 2025 EST
生成式 AI：不只是聊天机器人
Earned Nov 14, 2025 EST
Deploy an Agent with Agent Development Kit (ADK)
Earned Nov 14, 2025 EST
Extend Gemini Enterprise Assistant Capabilities
Earned Nov 12, 2025 EST
Edit images with Imagen
Earned Nov 11, 2025 EST
Understand and Respond to Media
Earned Nov 11, 2025 EST
Agent Summarization (Custom)
Earned Nov 11, 2025 EST
Integrate Agent Assist with Telephony and Chatbot Systems
Earned Nov 11, 2025 EST
Introduction to Agent Assist and its GenAI Capabilities
Earned Nov 10, 2025 EST
Generate and Edit Media in Vertex AI
Earned Nov 10, 2025 EST
Performance Measurement
Earned Nov 10, 2025 EST
Conversational AI Voice and Chat Integrations
Earned Nov 10, 2025 EST
Extend Conversational Agents Functionality with Webhooks and Tools
Earned Nov 10, 2025 EST
Engineer Effective Prompts for Generative Models
Earned Nov 10, 2025 EST
Explore Google's Gen AI Models
Earned Nov 10, 2025 EST
Deploy and Evaluate Model Garden Models
Earned Nov 9, 2025 EST
Supervised Fine-tuning for Gemini
Earned Nov 9, 2025 EST
利用 Vertex AI 实现机器学习运维 (MLOps)：模型评估
Earned Nov 9, 2025 EST
Model evaluation on Vertex AI
Earned Nov 9, 2025 EST
Stateful Flows
Earned Nov 7, 2025 EST
Generative Playbooks
Earned Nov 7, 2025 EST
Deploy a RAG application with vector search in Firestore
Earned Nov 7, 2025 EST
Implement Hybrid Search
Earned Nov 7, 2025 EST
Implement RAG with Vertex AI
Earned Nov 6, 2025 EST
使用 BigQuery 创建嵌入、向量搜索和 RAG
Earned Nov 6, 2025 EST
Analyze patterns in conversational data with Customer Experience Insights
Earned Nov 6, 2025 EST
Leverage data with Customer Experience Insights
Earned Nov 5, 2025 EST
Find, Explore and Deploy Model Garden Models
Earned Nov 5, 2025 EST
Configure AI Applications to optimize search results
Earned Nov 5, 2025 EST
Improve Vertex AI Search and Gemini Enterprise Search Results
Earned Nov 4, 2025 EST
Customer Experience with Google AI Architecture
Earned Nov 4, 2025 EST
Create and maintain Vertex AI Search data stores
Earned Nov 2, 2025 EST
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned Nov 2, 2025 EST
Introduction to NotebookLM
Earned Nov 2, 2025 EST
Create media search and media recommendations applications with AI Applications
Earned Nov 2, 2025 EST
Recommendations with AI Applications
Earned Oct 31, 2025 EDT
Build search and recommendations applications with AI Applications
Earned Oct 26, 2025 EDT
Vertex AI Search and Gemini Enterprise Analytics
Earned Oct 15, 2025 EDT
Vertex AI Search and Gemini Enterprise UI Configurations
Earned Oct 15, 2025 EDT
Create Data Stores for Gen AI Applications
Earned Oct 15, 2025 EDT
Introduction to AI Applications
Earned Oct 15, 2025 EDT
Deploy Google Agentspace
Earned Mar 30, 2025 EDT
借助 Gemini Enterprise 加速知识交流
Earned Mar 30, 2025 EDT
Webhook fundamentals
Earned Jul 23, 2024 EDT
Advanced Webhook Concepts
Earned Jul 23, 2024 EDT
Responsible AI: 和 Google Cloud 一起践行 AI 原则
Earned Feb 5, 2024 EST
Search with AI Applications
Earned Sep 15, 2023 EDT
GCC TechCon 2023 - Data - AI/ML
Earned Sep 14, 2023 EDT
Transformer 模型和 BERT 模型
Earned Jul 5, 2023 EDT
注意力机制
Earned Jul 5, 2023 EDT
负责任的 AI 简介
Earned Jul 5, 2023 EDT
大型语言模型简介
Earned Jul 5, 2023 EDT
Introduction to Generative AI - 简体中文
Earned Jul 5, 2023 EDT
Vertex AI Studio 简介
Earned Jul 5, 2023 EDT
Generative AI Fundamentals - 简体中文
Earned Jul 5, 2023 EDT
生成式 AI 简介
Earned Jul 4, 2023 EDT
图像生成简介
Earned Jul 3, 2023 EDT
创建图片标注模型
Earned Jul 3, 2023 EDT
编码器-解码器架构
Earned Jul 3, 2023 EDT
探索生成式 AI - Vertex AI
Earned Jul 3, 2023 EDT
Techcon 2023 Industry Game
Earned May 18, 2023 EDT
Techcon 2023 Platform Game
Earned May 17, 2023 EDT
Techcon 2023 Data & AI Game
Earned May 16, 2023 EDT
使用 Google Cloud Managed Service for Prometheus 来监控环境
Earned Mar 24, 2023 EDT
通过 BigQuery ML 创建机器学习模型
Earned Mar 12, 2023 EDT
在 Vertex AI 上构建和部署机器学习解决方案
Earned Mar 10, 2023 EST
借助 Firebase 开发无服务器应用
Earned Feb 13, 2023 EST
在 Google Cloud 上实施云安全基础措施
Earned Feb 11, 2023 EST
在 Cloud Run 上开发无服务器应用
Earned Feb 9, 2023 EST
为 Compute Engine 实现云负载均衡
Earned Feb 7, 2023 EST
在 Google Cloud 上部署 Kubernetes 应用
Earned Feb 7, 2023 EST
从 BigQuery 数据中挖掘数据洞见
Earned Feb 4, 2023 EST
使用 BigQuery 构建数据仓库
Earned Feb 1, 2023 EST
DEPRECATED Detect Manufacturing Defects Using Visual Inspection AI
Earned Jan 28, 2023 EST
用 Document AI 实现大规模自动数据采集
Earned Jan 27, 2023 EST
在 Google Cloud 上设置应用开发环境
Earned Jan 25, 2023 EST
开发 Google Cloud 网络
Earned Jan 20, 2023 EST
在 Google Cloud 上使用 Terraform 构建基础设施
Earned Jan 19, 2023 EST
创建和管理 Cloud Spanner 实例
Earned Jan 17, 2023 EST
用 Google Data Cloud 共享数据
Earned Dec 28, 2022 EST
Managing Cloud Infrastructure with Terraform
Earned Dec 25, 2022 EST
云架构：设计、实施和管理
Earned Dec 24, 2022 EST
利用 BigQuery ML 构建预测模型时的数据工程处理
Earned Dec 24, 2022 EST
为 Looker 信息中心和报告准备数据
Earned Dec 23, 2022 EST
在 Google Cloud 上使用 Machine Learning API
Earned Dec 21, 2022 EST
Migrating MySQL data to Cloud SQL using Database Migration Service
Earned Dec 8, 2022 EST
DEPRECATED Cloud Architecture
Earned Aug 27, 2022 EDT