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Thomas Chen

成为会员时间：2023

Contact Center as a Service Implementation Earned Oct 2, 2025 EDT
Advanced Performance Measurement Earned Sep 26, 2025 EDT
Customer Engagement Suite with Google AI Architecture Earned Sep 17, 2025 EDT
Analyze patterns in conversational data with Conversational Insights Earned Sep 17, 2025 EDT
Conversational Insights Earned Sep 12, 2025 EDT
Evaluate Gen AI model and agent performance Earned Sep 9, 2025 EDT
Edit images with Imagen Earned Sep 8, 2025 EDT
Performance Measurement Earned Sep 8, 2025 EDT
Build Gen AI solutions using Model Garden models and APIs Earned Sep 8, 2025 EDT
Conversational AI on Vertex AI and Dialogflow CX Earned Sep 4, 2025 EDT
Improve Performance by Fine-Tuning Foundation Models Earned Sep 3, 2025 EDT
Build basic Conversational Agents with Playbooks and Flows Earned Aug 29, 2025 EDT
Virtual FAQ with data store agents Earned Aug 28, 2025 EDT
Incorporate Generative Features into Conversational Agent flows Earned Aug 28, 2025 EDT
Stateful Flows Earned Aug 27, 2025 EDT
Generative Playbooks Earned Aug 26, 2025 EDT
Conversational AI and its Engagement Framework Earned Aug 25, 2025 EDT
Engineer Effective Prompts for Generative Models Earned Aug 1, 2025 EDT
Explore Google's Gen AI Models Earned Aug 1, 2025 EDT
Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine Earned Jul 21, 2025 EDT
Orchestrate LLM solutions with LangChain Earned Jul 18, 2025 EDT
Orchestrating Gen AI Applications with LangChain Earned Jul 14, 2025 EDT
Build generative virtual agents with API integrations Earned Jun 14, 2025 EDT
Introduction to CES and Conversational Agents Earned Jun 10, 2025 EDT
Deploy Google Agentspace Earned Jun 5, 2025 EDT
借助 Agentspace 加速知识交流 Earned May 27, 2025 EDT
Introduction to Google Distributed Cloud connected Earned Oct 16, 2024 EDT
编码器-解码器架构 Earned Aug 15, 2024 EDT
注意力机制 Earned Aug 13, 2024 EDT
在 Vertex AI 中设计提示 Earned Aug 6, 2024 EDT
Generative AI Fundamentals Earned Aug 3, 2024 EDT
Build and Deploy a Generative AI solution using a RAG framework Earned Jun 25, 2024 EDT
Building Gen AI Apps with Vertex AI: Prompting and Tuning Earned Jun 24, 2024 EDT
图像生成简介 Earned Jun 17, 2024 EDT
Chronicle SIEM Fundamentals Earned Jun 16, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps Earned Jun 14, 2024 EDT
Text Prompt Engineering Techniques Earned May 17, 2024 EDT
Vertex AI Studio 简介 Earned May 11, 2024 EDT
Generative AI for Business Leaders Earned May 11, 2024 EDT
Responsible AI: 和 Google Cloud 一起践行 AI 原则 Earned May 9, 2024 EDT
负责任的 AI 简介 Earned May 7, 2024 EDT
大型语言模型简介 Earned May 7, 2024 EDT
生成式 AI 简介 Earned May 3, 2024 EDT
VM Migration for Partners Earned Apr 11, 2023 EDT
Deploying and Managing Google Cloud VMware Engine Earned Apr 6, 2023 EDT

An AI-driven Contact Center as a Service (CCaaS) solution that is built natively on Google Cloud. The Implementation course provides Partners with essential training about the delivery of key features and functionality. The course explores how to leverage your key understanding of the product into successful customer implementation engagements with tips, best practices, guides, and more. Note: This product was previously called Contact Center AI (CCAI) Platform you may see references to that name still in the course, however the course is technically correct.

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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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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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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 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 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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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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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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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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In this course you will learn how to use the new generative AI features in Dialogflow CX to create virtual agents that can have more natural and engaging conversations with customers. Discover how to deploy generative fallback responses to gracefully handle errors and omissions in customer conversations, deploy generators to increase intent coverage, and structure, ingest, and manage data in a data store. And explore how to deploy and maintain generative AI agents using your data, and deploy and maintain hybrid agents in combination with existing intent-based design paradigms.

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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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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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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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Transform your understanding of customer service with this course on the Customer Engagement Suite (CES) and its powerful generative AI capabilities. You'll start by tracing the journey of contact centers, understanding how they've evolved and where gen AI is propelling them next. Then, you'll gain a deep understanding of the core building blocks within the CES solution, seeing how each component contributes to delivering exceptional customer experiences. The course concludes by exploring the robust business case for CES, along with practical use cases and the various user personas that benefit from this innovative solution.

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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 course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Vertex AI Agent Engine to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Engine. Please note these labs are based off a pre-released version of this product. There may be some lag on these labs as we provide maintenance updates.

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Learn to use LangChain to call Google Cloud LLMs and Generative AI Services and Datastores to simplify complex applications' code.

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This course equips full-stack mobile and web developers with the skills to integrate generative AI features into their applications using LangChain. You'll learn how to leverage LangChain’s capabilities for backend flows and seamless model execution, all within the familiar environment of Python. The course guides you through the entire process, from prototyping to production, ensuring a smooth journey in building next-generation AI-powered applications.

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Demonstrate the ability to create and deploy generative virtual agents with natural language using Vertex AI Agent Builder and augment responses by integrating Gemini responses with third party APIs and your own data stores You will use the following technologies and Google Cloud services: Vertex AI Agent Builder Gemini Cloud Functions

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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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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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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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In this course, you will learn about GDC connected (previously known as GDC Edge), an offering from Google Distributed Cloud. This course provides both a business and technical overview of GDC connected, exploring its key features and target customers. Participants will gain insights into GDC connected's value proposition and learn how to effectively communicate its benefits to potential clients, enabling them to qualify for sales opportunities.

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本课程简要介绍了编码器-解码器架构，这是一种功能强大且常见的机器学习架构，适用于机器翻译、文本摘要和问答等 sequence-to-sequence 任务。您将了解编码器-解码器架构的主要组成部分，以及如何训练和部署这些模型。在相应的实验演示中，您将在 TensorFlow 中从头编写简单的编码器-解码器架构实现代码，以用于诗歌生成。

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

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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.

了解详情

Demonstrate your ability to implement updated prompt engineering techniques and utilize several of Gemini's key capacilities including multimodal understanding and function calling. Then integrate generative AI into a RAG application deployed to Cloud Run. This course contains labs that are to be used as a test environment. They are deployed to test your understanding as a learner with a limited scope. These technologies can be used with fewer limitations in a real world environment.

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(This course was previously named Multimodal Prompt Engineering with Gemini and PaLM) This course teaches how to use Vertex AI Studio, a Google Cloud console tool for rapidly prototyping and testing generative AI models. You learn to test sample prompts, design your own prompts, and customize foundation models to handle tasks that meet your application's needs. Whether you are looking for text, chat, code, image or speech generative experiences Vertex AI Studio offers you an interface to work with and APIs to integrate your production application.

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

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This course will provide you with an overview of SIEM technology to set the stage for the differentiation and expansion of capabilities that Chronicle SIEM provides.

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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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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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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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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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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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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 provides comprehensive skills on VM migration, from the initial assessment through the final implementation through presentations, demonstrations, and whiteboard session.

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This course enables partners to help customers extend their on-premises VMware environments to Google Cloud using Google Cloud VMware Engine. Partners will learn how to architect Google Cloud VMware Engine migration solutions that allow customers to move virtual machines to the cloud with minimal risk. The course also instructs partners on how to solve real-world VMware integration and migration problems.

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