Introduction to AI Applications
Earned Aug 8, 2025 EDT
Vertex AI Search and Gemini Enterprise Analytics
Earned Jul 4, 2025 EDT
運用 Gemini Enterprise 加速知識交流
Earned Jun 27, 2025 EDT
運用 Agent Development Kit (ADK) 與 Agent Engine 部署多代理系統
Earned May 12, 2025 EDT
Build and Deploy a Generative AI solution using a RAG framework
Earned Nov 19, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Nov 5, 2024 EST
Text Prompt Engineering Techniques
Earned Nov 5, 2024 EST
Data Warehousing for Partners: Enable Google Cloud Customers
Earned Apr 8, 2024 EDT
MySQL to Cloud SQL
Earned Mar 28, 2024 EDT
Document AI: Building a Custom Document Extractor
Earned Mar 18, 2024 EDT
為 Looker 資訊主頁和報表準備資料
Earned Aug 17, 2023 EDT
Cloud SQL
Earned Apr 7, 2023 EDT
建立及管理 Cloud Spanner 執行個體
Earned Apr 3, 2023 EDT
Google Cloud 基礎知識：核心基礎架構
Earned Mar 27, 2023 EDT
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.)
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.)
了解详情
Gemini Enterprise 結合 Google 的搜尋和 AI 輔助功能，企業員工只要在單一搜尋列輸入關鍵字，就能查找文件儲存空間、電子郵件、對話、支援單處理系統和其他資料來源中的特定資訊。Gemini Enterprise 助理還能協助人員腦力激盪、研究資訊、列出文件大綱及執行其他動作，例如邀請同事加入日曆活動，加快完成知識型工作及各種協作作業。(請注意，Gemini Enterprise 先前稱為 Google Agentspace，本課程可能會提及產品舊稱。)
了解详情
本課程說明如何使用 Google Agent Development Kit 建構複雜的多代理系統。您將建構配備工具的虛擬服務專員，並透過從屬關係和流程定義互動方式。您將在本機執行代理，並部署至 Vertex AI Agent Engine，透過代管代理流程執行；Agent Engine 則處理基礎架構決策和資源調度作業。
請注意，這些實驗室是根據這項產品的預先發布版製成。我們會進行維護更新，因此這些研究室將可能出現延遲。
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.
了解详情
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.
了解详情
Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
了解详情
This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.
了解详情
Migration from MySQL to Cloud SQL using Database Migration Service that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.
了解详情
This workload aims to upskill Google Cloud partners to perform specific tasks associated with building a Custom Doc Extractor using the Google Cloud AI solution. The following will be addressed:
Service: Document AI
Task: Extract fields
Processors: Custom Document Extractor and Document Splitter
Prediction: Using Endpoint to programmatically extract fields
Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.
Introduction to AI Applications
Earned Aug 8, 2025 EDT
Vertex AI Search and Gemini Enterprise Analytics
Earned Jul 4, 2025 EDT
運用 Gemini Enterprise 加速知識交流
Earned Jun 27, 2025 EDT
運用 Agent Development Kit (ADK) 與 Agent Engine 部署多代理系統
Earned May 12, 2025 EDT
Build and Deploy a Generative AI solution using a RAG framework
Earned Nov 19, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Nov 5, 2024 EST
Text Prompt Engineering Techniques
Earned Nov 5, 2024 EST
Data Warehousing for Partners: Enable Google Cloud Customers
Earned Apr 8, 2024 EDT
MySQL to Cloud SQL
Earned Mar 28, 2024 EDT
Document AI: Building a Custom Document Extractor
Earned Mar 18, 2024 EDT
為 Looker 資訊主頁和報表準備資料
Earned Aug 17, 2023 EDT
Cloud SQL
Earned Apr 7, 2023 EDT
建立及管理 Cloud Spanner 執行個體
Earned Apr 3, 2023 EDT
Google Cloud 基礎知識：核心基礎架構
Earned Mar 27, 2023 EDT