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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This is an introductory course to all solutions in the Conversational AI portfolio and the Gen AI features that are available to transform them. The course also explores the business case around Conversational AI, and the use cases and user personas addressed by the solution. 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 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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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.
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This is a introductory course to all solutions in the Contact Centre AI (CCAI) portfolio and the Generative AI features that are poised to transform them. The course also explores the CCAI go to market and engagement model, the business case around CCAI, as well as the use cases and user personas addressed by the solution.
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完成 在 Vertex AI 設計提示 技能徽章入門課程，即可證明您具備下列技能： 在 Vertex AI 設計提示、分析圖片，以及運用多模態模型生成內容。瞭解如何建立有效的提示、引導生成式 AI 輸出內容， 以及將 Gemini 模型用於實際的行銷情境。 「技能徽章」是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品與服務方面的精通程度， 代表您已通過測驗，能在互動式實作環境中應用相關知識。完成 本課程及結業評量挑戰研究室，即可取得技能徽章 並與親友分享。
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探索生成式 AI - Vertex AI 課程包含一系列實驗室，幫助您瞭解 如何在 Google Cloud 使用生成式 AI。透過實驗室，您將瞭解 如何使用 Vertex AI PaLM API 系列模型，包括 text-bison、chat-bison、 和 textembedding-gecko。您也會瞭解提示設計、最佳做法、 以及這些模型如何用於構思、文字分類、文字擷取、文字 摘要等。您也會瞭解如何透過 Vertex AI 自訂訓練功能調整基礎模型， 並將模型部署至 Vertex AI 端點。
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Welcome to "CCAI Virtual Agent Development in Dialogflow ES for Software Developers", the third course in the "Customer Experiences with Contact Center AI" series.
In this course, learn to use additional features of Dialogflow ES for your virtual agent, create a Firestore instance to store customer data, and implement cloud functions that access the data. With the ability to read and write customer data, learner’s virtual agents are conversationally dynamic and able to defer contact center volume from human agents. You'll be introduced to methods for testing your virtual agent and logs which can be useful for understanding issues that arise. Lastly, learn about connectivity protocols, APIs, and platforms for integrating your virtual agent with services already established for your business.
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Welcome to "Virtual Agent Development in Dialogflow ES for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series.
In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will use Dialogflow ES to create virtual agents and test them using the Dialogflow ES simulator. This course also provides best practices on developing virtual agents. You will also be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations. Through a combination of presentations, demos, and hands-on labs, participants learn how to create virtual agents.
This is an intermediate course, intended for learners with the following types of roles:
Conversational designers: Designs the user experience of a virtual assistant. Translates the brand's business requirements into natural dialog flows.
Citizen developers: Creates new business applications fo…
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This course explores Google Cloud technologies to create and generate embeddings. Embeddings are numerical representations of text, images, video and audio, and play a pivotal role in many tasks that involve the identification of similar items, like Google searches, online shopping recommendations, and personalized music suggestions. Specifically, you’ll use embeddings for tasks like classification, outlier detection, clustering and semantic search.
You’ll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) systems and question-answering solutions, on your own proprietary data using Google Cloud’s Vertex AI.
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這堂課程會介紹 AI 搜尋技術、工具和應用程式。主題涵蓋使用向量嵌入執行語意搜尋；結合語意和關鍵字做法的混合型搜尋機制；以及運用檢索增強生成 (RAG) 技術建構有基準的 AI 代理，盡可能減少 AI 幻覺。您可以實際使用 Vertex AI Vector Search，打造智慧型搜尋引擎。
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Welcome to "CCAI Conversational Design Fundamentals", the first course in the "Customer Experiences with Contact Center AI" series.
In this course, learn how to design customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will be introduced to CCAI and its three pillars (Dialogflow, Agent Assist, and Insights), and the concepts behind conversational experiences and how the study of them influences the design of your virtual agent. After taking this course you will be prepared to take your virtual agent design to the next level of intelligent conversation.
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This course explores the Geographic Information Systems (GIS), GIS Visualization, and machine learning enhancements to BigQuery.
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This course explores how to implement a streaming analytics solution using Dataflow and BigQuery.
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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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This course explores how to implement a streaming analytics solution using Pub/Sub.
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This course continues to explore the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataflow.
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This course continues to explore the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Cloud Data Fusion.
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This course explores the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataproc.
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This course identifies best practices for migrating data warehouses to BigQuery and the key skills required to perform successful migration.
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Welcome to Optimize in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on optimization.
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Welcome to Design in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on schema design.
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This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.
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This course will help ML Engineers, Developers, and Data Scientists implement Large Language Models for Generative AI use cases with Vertex AI. The first two modules of this course contain links to videos and prerequisite course materials that will build your knowledge foundation in Generative AI. Please do not skip these modules. The advanced modules in this course assume you have completed these earlier modules.
本課程將介紹擴散模型，這是一種機器學習模型，近期在圖像生成領域展現亮眼潛力。概念源自物理學，尤其深受熱力學影響。過去幾年來，在學術界和業界都是炙手可熱的焦點。在 Google Cloud 中，擴散模型是許多先進圖像生成模型和工具的基礎。課程將介紹擴散模型背後的理論，並說明如何在 Vertex AI 上訓練和部署這些模型。
本課程會介紹 Vertex AI Studio。您可以運用這項工具和生成式 AI 模型互動、根據商業構想設計原型，並投入到正式環境。透過身歷其境的應用實例、有趣的課程及實作實驗室，您將能探索從提示到正式環境的生命週期，同時學習如何將 Vertex AI Studio 運用在多模態版 Gemini 應用程式、提示設計、提示工程和模型調整。這個課程的目標是讓您能運用 Vertex AI Studio，在專案中發揮生成式 AI 的潛能。
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隨著企業持續擴大使用人工智慧和機器學習，以負責任的方式發展相關技術也日益重要。對許多企業來說，談論負責任的 AI 技術可能不難，如何付諸實行才是真正的挑戰。如要瞭解如何在機構中導入負責任的 AI 技術，本課程絕對能助您一臂之力。
您可以從中瞭解 Google Cloud 目前採取的策略、最佳做法和經驗談，協助貴機構奠定良好基礎，實踐負責任的 AI 技術。
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這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性，以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。
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這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。
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這是一堂入門級的微學習課程，旨在探討大型語言模型 (LLM) 的定義和用途，並說明如何調整提示來提高 LLM 成效。此外，也會介紹多項 Google 工具，協助您自行開發生成式 AI 應用程式。
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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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In this course, you'll use text embeddings for tasks like classification, outlier detection, text clustering and semantic search. You'll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) solutions, such as for question-answering systems, using Google Cloud's Vertex AI and Google Cloud databases.
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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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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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(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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(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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This content is deprecated. Please see the latest version of the course, here.
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本課程將介紹擴散模型，這是一種機器學習模型，近期在圖像生成領域展現亮眼潛力。概念源自物理學，尤其深受熱力學影響。過去幾年來，在學術界和業界都是炙手可熱的焦點。在 Google Cloud 中，擴散模型是許多先進圖像生成模型和工具的基礎。課程將介紹擴散模型背後的理論，並說明如何在 Vertex AI 上訓練和部署這些模型。
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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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本課程會介紹 Vertex AI Studio。您可以運用這項工具和生成式 AI 模型互動、根據商業構想設計原型，並投入到正式環境。透過身歷其境的應用實例、有趣的課程及實作實驗室，您將能探索從提示到正式環境的生命週期，同時學習如何將 Vertex AI Studio 運用在多模態版 Gemini 應用程式、提示設計、提示工程和模型調整。這個課程的目標是讓您能運用 Vertex AI Studio，在專案中發揮生成式 AI 的潛能。
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隨著企業持續擴大使用人工智慧和機器學習，以負責任的方式發展相關技術也日益重要。對許多企業來說，談論負責任的 AI 技術可能不難，如何付諸實行才是真正的挑戰。如要瞭解如何在機構中導入負責任的 AI 技術，本課程絕對能助您一臂之力。
您可以從中瞭解 Google Cloud 目前採取的策略、最佳做法和經驗談，協助貴機構奠定良好基礎，實踐負責任的 AI 技術。
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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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這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性，以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。
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這是一堂入門級的微學習課程，旨在探討大型語言模型 (LLM) 的定義和用途，並說明如何調整提示來提高 LLM 成效。此外，也會介紹多項 Google 工具，協助您自行開發生成式 AI 應用程式。
了解详情
這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。
在 Vertex AI 使用 Gemini API 探索生成式 AI
Earned May 28, 2025 EDT
使用 Gemini 多模態功能和多模態 RAG 檢查複合型文件
Earned May 16, 2025 EDT
Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine
Earned May 16, 2025 EDT
Intro to Conversational AI and Conversational AI Engagement Framework
Earned Mar 17, 2025 EDT
Analyzing and Visualizing Data in Looker
Earned Mar 12, 2025 EDT
Digital Transformation with Google Cloud
Earned Mar 7, 2025 EST
Intro to CCAI and CCAI Engagement Framework
Earned Dec 16, 2024 EST
在 Vertex AI 設計提示
Earned Aug 5, 2024 EDT
探索生成式 AI - Vertex AI
Earned Mar 10, 2024 EDT
Virtual Agent Development in Dialogflow ES for Software Devs
Earned Mar 9, 2024 EST
Virtual Agent Development in Dialogflow ES for Citizen Devs
Earned Mar 8, 2024 EST
Custom Search with Embeddings in Vertex AI
Earned Mar 8, 2024 EST
Vector Search 和嵌入
Earned Mar 7, 2024 EST
Contact Center AI: Conversational Design Fundamentals
Earned Feb 28, 2024 EST
Data Warehousing for Partners: BigQuery Extended Capabilities
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Streaming Analytics
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Analyze Data with Looker
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Stream Data with Pub/Sub
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Process Data with Dataflow
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Cloud Data Fusion Pipelines
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Process Data with Dataproc
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Migrate Data to BigQuery
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Optimize in BigQuery
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Design in BigQuery
Earned Feb 27, 2024 EST
Data Warehousing for Partners: Enable Google Cloud Customers
Earned Feb 27, 2024 EST
Implementing Generative AI with Vertex AI
Earned Feb 26, 2024 EST
建立圖像說明生成模型
Earned Feb 26, 2024 EST
Transformer 和 BERT 模型
Earned Feb 26, 2024 EST
圖像生成簡介
Earned Feb 26, 2024 EST
編碼器-解碼器架構
Earned Feb 26, 2024 EST
注意力機制
Earned Feb 26, 2024 EST
Vertex AI Studio 簡介
Earned Feb 26, 2024 EST
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則
Earned Feb 26, 2024 EST
負責任的 AI 技術簡介
Earned Feb 26, 2024 EST
生成式 AI 簡介
Earned Feb 26, 2024 EST
大型語言模型簡介
Earned Feb 26, 2024 EST
Text Prompt Engineering Techniques
Earned Feb 26, 2024 EST
Develop Advanced Enterprise Search and Conversation Applications
Earned Jan 10, 2024 EST
Introduction to CES and Conversational Agents
Earned Jan 10, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Jan 10, 2024 EST
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned Jan 8, 2024 EST
Search with AI Applications
Earned Jan 5, 2024 EST
Generative AI Explorer : Vertex AI
Earned Jan 4, 2024 EST
圖像生成簡介
Earned Nov 21, 2023 EST
Generative AI for Business Leaders
Earned Nov 21, 2023 EST
Vertex AI Studio 簡介
Earned Nov 17, 2023 EST
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則
Earned Nov 17, 2023 EST
Generative AI Fundamentals
Earned Nov 16, 2023 EST
負責任的 AI 技術簡介
Earned Nov 16, 2023 EST
大型語言模型簡介
Earned Nov 16, 2023 EST
生成式 AI 簡介
Earned Nov 16, 2023 EST