Architecting with Google Kubernetes Engine: Foundations - 繁體中文
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 建構資料網格
Earned Feb 2, 2024 EST
開始使用 Dataplex
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
使用 Gemini：端對端 SDLC
Earned Jan 15, 2024 EST
使用 Gemini：DevOps 工程師
Earned Jan 15, 2024 EST
使用 Gemini：網路工程師
Earned Jan 15, 2024 EST
Achieving Advanced Insights with BigQuery
Earned Jan 15, 2024 EST
在 Google Cloud 為機器學習 API 準備資料
Earned Jan 11, 2024 EST
使用 BigQuery ML 為預測模型進行資料工程
Earned Jan 10, 2024 EST
使用 Gemini：數據資料學家和分析師
Earned Jan 10, 2024 EST
使用 Gemini：資安工程師
Earned Jan 10, 2024 EST
Gemini in Google Slides
Earned Jan 8, 2024 EST
使用 Gemini：應用程式開發人員
Earned Jan 8, 2024 EST
Gemini for Google Workspace 簡介
Earned Jan 8, 2024 EST
Gemini in Gmail
Earned Jan 8, 2024 EST
Gemini in Google Docs
Earned Jan 8, 2024 EST
Gemini in Google Sheets
Earned Jan 8, 2024 EST
使用 Gemini：雲端架構師
Earned Jan 8, 2024 EST
透過 BigQuery 建構資料倉儲
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
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則
Earned Dec 14, 2023 EST
負責任的 AI 技術簡介
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
透過 Vertex AI 建構及部署機器學習解決方案
Earned Jun 15, 2023 EDT
建立 Google Cloud 網路
Earned Jun 1, 2023 EDT
Certification Learning Path: Professional Cloud DevOps Engineer
Earned May 30, 2023 EDT
透過 Google Cloud Observability 監控及記錄系統狀態
Earned May 29, 2023 EDT
在 Google Cloud 實作 DevOps 工作流程
Earned May 26, 2023 EDT
DEPRECATED Cloud Operations and Service Mesh with Anthos
Earned May 25, 2023 EDT
可靠的 Google Cloud 基礎架構：設計與程序
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
從 BigQuery 資料取得深入分析結果
Earned Feb 9, 2023 EST
Launching into Machine Learning
Earned Feb 9, 2023 EST
運用 BigQuery ML 建立機器學習模型
Earned Jan 27, 2023 EST
為 Looker 資訊主頁和報表準備資料
Earned Jan 27, 2023 EST
Applying Machine Learning to your Data with Google Cloud
Earned Jan 26, 2023 EST
使用 BigQuery 進行機器學習
Earned Jan 25, 2023 EST
重要的 Google Cloud 基礎架構：核心服務
Earned Nov 22, 2022 EST
Getting Started with Terraform for Google Cloud
Earned Nov 21, 2022 EST
在 Google Cloud 使用 Terraform 建構基礎架構
Earned Oct 4, 2022 EDT
在 Compute Engine 實作負載平衡功能
Earned Oct 3, 2022 EDT
Google Cloud Essentials
Earned Oct 3, 2022 EDT
在 Google Cloud 設定應用程式開發環境
Earned Aug 5, 2022 EDT
Scaling with Google Cloud Operations
Earned Aug 4, 2022 EDT
開始使用 Google Kubernetes Engine
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 基礎知識：核心基礎架構
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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本課程會說明如何使用 Google 可攜式 UI 工具包 Flutter 來開發應用程式，並將應用程式與 Google 生成式 AI 模型系列 Gemini 整合。您也會用到 Vertex AI Agent Builder，此為建構及管理 AI 代理和應用程式的 Google 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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這堂課程會說明 BigQuery 中的檢索增強生成 (RAG) 解決方案，協助您減少 AI 幻覺。當中介紹的 RAG 工作流程包含建立嵌入項目、搜尋向量空間，以及生成更符合需求的答案。另外，這堂課程會解釋這些步驟背後的概念與原因，以及實際運用 BigQuery 實作的方法。完成課程之後，學員將學會使用 BigQuery，以及 Gemini 和嵌入模型等生成式 AI 模型，建立 RAG pipeline 來處理自己的 AI 幻覺應用實例。
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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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本課程針對評估生成式和預測式 AI 模型，向機器學習從業人員介紹相關的基礎工具、技術和最佳做法。模型評估是機器學習的重要領域，確保這類系統能在正式環境中提供可靠、準確且成效優異的結果。
學員將深入瞭解多種評估指標與方法，以及適用於不同模型類型和工作的應用方式。此外，也會特別介紹生成式 AI 模型帶來的獨特難題，並提供有效的應對策略。透過 Google Cloud Vertex AI 平台，學員將瞭解在模型挑選、最佳化和持續監控方面，該如何導入穩健的評估程序。
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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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本課程涵蓋「AI 隱私權」和「AI 安全性」這兩個重要主題。我們將介紹實用的方法和工具，協助您運用 Google Cloud 產品和開放原始碼工具，導入 AI 隱私權和安全性的建議做法。
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本課程旨在說明 AI 的可解釋性和透明度概念、探討 AI 透明度對開發人員和工程師的重要性。課程中也會介紹實務方法和工具，有助於讓資料和 AI 模型透明且可解釋。
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本課程旨在提供必要的知識和工具，協助您探索機器學習運作團隊在部署及管理生成式 AI 模型時面臨的獨特挑戰，並瞭解 Vertex AI 如何幫 AI 團隊簡化機器學習運作程序，打造成效非凡的生成式 AI 專案。
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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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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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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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 結合 Google 的搜尋和 AI 專業知識，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。Agentspace 助理還能協助發想創意、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，並協作各種內容。
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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 實作 Cloud 安全防護措施：基礎知識 技能徽章中階課程， 即可證明您具備下列技能：運用 Identity and Access Management (IAM) 建立及指派角色、 建立及管理服務帳戶、啟用虛擬私有雲 (VPC) 網路中的私人連線、 運用 Identity-Aware Proxy 限制應用程式存取權、 運用 Cloud Key Management Service (KMS) 管理金鑰和已加密資料，以及建立私人 Kubernetes 叢集。 「技能徽章」是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和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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在本課程中，您會學到 Google Cloud 上的資料工程、資料工程師的角色與職責，以及這些內容如何對應至 Google Cloud 提供的服務。您也將瞭解處理資料工程難題的許多方法。
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如果您是剛起步的雲端開發人員， 想在 Google Cloud Essentials 外獲得更多實作經驗，歡迎參加本課程。您將透過實作實驗室， 深入瞭解 Cloud Storage 和其他重要應用程式服務，例如： Monitoring 和 Cloud Functions。您將習得 在任何 Google Cloud 專案都適用的寶貴技能。
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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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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.
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「以串流方式將分析資料傳入 BigQuery」任務，即可獲得技能徽章。 您將結合使用 Pub/Sub、Dataflow 和 BigQuery，以串流方式傳送 資料以供分析。 「技能徽章」是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和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。完成這個技能徽章課程和結業評量挑戰實驗室之後， 即可取得技能徽章並與他人分享。
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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「開始使用 Pub/Sub」任務，即可獲得 技能徽章。 您將瞭解如何透過 Cloud 控制台使用 Pub/Sub，以及如何使用 Cloud Scheduler 工作節省心力，而 Pub/Sub Lite 則能為大量事件擷取作業。節省費用。 「技能徽章」是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和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。完成這個技能徽章課程和結業評量挑戰實驗室之後， 即可取得技能徽章並與他人分享。
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完成「開始使用 API Gateway」任務，即可獲得技能徽章。 瞭解如何使用 API Gateway，透過全代管閘道部署、保護及管理 API 。 技能徽章是 Google Cloud 核發的 獨家數位徽章，用於肯定您對於 Google Cloud 產品與服務的精通程度。 獲得技能徽章代表您已通過測驗，能在互動式實作環境 應用相關知識。完成這個技能徽章課程和結業評量挑戰實驗室之後， 即可取得數位徽章並與他人分享。
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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 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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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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本課程介紹 Google Cloud 中的 AI 和機器學習 (ML) 服務。這些服務可建構預測式和生成式 AI 專案。我們將帶您探索「從資料到 AI」生命週期中適用的技術、產品和工具，包括 AI 基礎、開發選項及解決方案。課程目的是藉由生動的學習體驗與實作練習，增進數據資料學家、AI 開發人員和機器學習工程師的技能與知識。
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完成「建構安全的 Google Cloud 網路」課程，即可獲得技能徽章。本課程將說明多項網路相關 資源，協助您在 Google Cloud 建構、調度資源和保護應用程式。 「技能徽章」是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和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 這個技能徽章課程和結業評量挑戰實驗室，即可取得數位徽章 並與他人分享。
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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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這堂初級課程將介紹 Google Cloud 的資料分析工作流程，以及用於探索、分析資料並以圖表呈現的工具。您也能學會如何與相關人員分享自己的發現結果。本課程包含個案研究、實作實驗室、講座、測驗和示範，實際展示如何將原始資料集轉化為清晰的資料，進而呈現出能發揮成效的圖表和資訊主頁。無論您是資料領域從業人員、想瞭解如何透過 Google Cloud 取得成功，或有意在職涯中更上一層樓，本課程都能協助您踏出第一步。絕大多數在工作上執行或運用資料分析的學員，都能從本課程受益。
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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.
完成 在 Google Cloud 部署 Kubernetes 應用程式 技能徽章中階課程，即可證明您具備下列技能： 設定及建構 Docker 容器映像檔、建立及管理 Google Kubernetes Engine (GKE) 叢集、運用 kubectl 有效 管理叢集，以及運用強大的持續推送軟體更新做法來部署 Kubernetes 應用程式。 「技能徽章」是 Google Cloud 核發的獨家數位徽章，用於肯定您在 Google Cloud 產品和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。 完成這個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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在 「Google Kubernetes Engine 架構：基礎知識」的課程中，您將復習 Google Cloud 的配置和原則，接著是建立和管理軟體容器簡介和 Kubernetes 架構簡介。
這是 Google Kubernetes Engine 架構系列中的第一項課程。完成此課程後，請註冊 Google Kubernetes Engine 架構：工作負載課程。
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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「使用 Dataplex 建構資料網格」技能徽章入門課程，即可證明您具備下列技能：使用 Dataplex 建構資料網格， 以利在 Google Cloud 維護資料安全性，並協助治理和探索資料。您將練習並測試自己的技能，包括在 Dataplex 為資產加上標記、指派 IAM 角色，以及評估資料品質。 「技能徽章」是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和服務方面的精熟技能， 代表您已通過測驗，能在互動式實作環境應用相關知識。完成這個技能 徽章課程和結業評量挑戰實驗室，即可取得數位徽章 並與他人分享。
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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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助您透過 Google Cloud 使用 Google 產品和服務，開發、測試、部署及管理應用程式。有了 Gemini 的協助，您會學到如何開發和建構網頁應用程式、修正應用程式中的錯誤、開發測試及查詢資料。在實作研究室中，您也會體驗到 Gemini 如何改良軟體開發生命週期 (SDLC)。
Duet AI 已更名為 Gemini，這是我們的新一代模型。
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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助工程師透過 Google Cloud 管理基礎架構。您將學到如何透過提示讓 Gemini 尋找和瞭解應用程式記錄檔、建立 GKE 叢集，以及研究如何打造建構環境。在實作研究室中，您也會瞭解 Gemini 如何改良開發運作的工作流程。
Duet AI 已更名為 Gemini，是我們新一代的模型。
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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助網路工程師建立、更新及維護虛擬私有雲網路。您將瞭解如何透過提示讓 Gemini 為網路工作提供指引，獲得比搜尋結果更具體的資訊。在實作研究室中，您也會體驗到 Gemini 如何簡化 Google Cloud 虛擬私有雲網路的作業。
Duet AI 已更名為 Gemini，這是我們的新一代模型。
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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 在 Google Cloud 為機器學習 API 準備資料 技能徽章入門課程，即可證明您具備下列技能： 使用 Dataprep by Trifacta 清理資料、在 Dataflow 執行資料管道、在 Dataproc 建立叢集和執行 Apache Spark 工作，以及呼叫機器學習 API，包含 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。 「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。完成本技能徽章課程及結業評量挑戰研究室， 即可取得技能徽章並與他人分享。
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完成使用 BigQuery ML 為預測模型進行資料工程技能徽章中階課程， 即可證明自己具備下列知識與技能：運用 Dataprep by Trifacta 建構連至 BigQuery 的資料轉換 pipeline； 使用 Cloud Storage、Dataflow 和 BigQuery 建構「擷取、轉換及載入」(ETL) 工作負載， 以及使用 BigQuery ML 建構機器學習模型。技能 徽章是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和服務方面的精熟技能， 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 這個課程及結業評量挑戰實驗室，即可取得數位徽章 並與他人分享。
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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助分析客戶資料及預測產品銷售情形。您也會學習如何在 BigQuery 中使用客戶資料識別、分類及開發新客戶。透過使用實作研究室，您可以體驗 Gemini 如何改良資料分析和機器學習工作流程。
Duet AI 已更名為 Gemini，這是我們的新一代模型。
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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助您透過 Google Cloud 保護雲端環境和資源。您將學到如何將工作負載範例部署到 Google Cloud 中的環境，以及運用 Gemini 找出並修復安全性設定錯誤。在實作研究室中，您也會體驗到 Gemini 如何改良雲端安全防護機制。
Duet AI 已更名為 Gemini，這是我們的新一代模型。
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Gemini 版 Google Workspace 是一項外掛程式，可讓客戶在 Google Workspace 使用生成式 AI 功能。這堂迷你課程會介紹 Gemini 的主要功能，並說明如何在 Google 簡報善用這些功能，提高生產力和效率。
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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助開發人員透過 Google Cloud 建構應用程式。您將瞭解如何透過提示讓 Gemini 為您解釋程式碼內容、推薦 Google Cloud 服務，以及生成應用程式的程式碼。在實作研究室中，您也會體驗到 Gemini 如何改良應用程式的開發工作流程。
Duet AI 已更名為 Gemini，這是我們的新一代模型。
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客戶能透過 Gemini 版 Google Workspace 外掛程式在 Google Workspace 使用生成式 AI 功能。本學習路徑會介紹 Gemini 的主要功能，並說明如何在 Google Workspace 善用這些功能，提高生產力和效率。
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Gemini 版 Google Workspace 是一項外掛程式，可讓客戶在 Google Workspace 使用生成式 AI 功能。這堂迷你課程會介紹 Gemini 的主要功能，並說明如何在 Gmail 善用這些功能，提高生產力和效率。
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使用者將能透過 Gemini 版 Google Workspace 外掛程式運用生成式 AI 功能。本課程會使用影片、實作活動和練習範例，深入介紹 Gemini 版 Google 文件的功能。您將學到如何透過 Gemini 使用提示生成撰寫內容、編輯寫好的文字，以提升整體工作效率。本課程結束後，您將具備 Gemini 版 Google 文件的知識及技能，可自信地運用這項工具提升寫作品質。
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安裝 Gemini 版 Google Workspace 外掛程式後，客戶就能在 Google Workspace 使用生成式 AI 功能。這堂迷你課程會介紹 Gemini 的主要功能，並說明如何在 Google 試算表善用這些功能，提高生產力和效率。
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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助管理員在 Google Cloud 佈建基礎架構。您將瞭解如何透過提示讓 Gemini 解釋基礎架構、部署 GKE 叢集，以及更新既有的基礎架構。在實作研究室中，您也會體驗到 Gemini 如何改良 GKE 的部署工作流程。
Duet AI 已更名為 Gemini，這是我們的新一代模型。
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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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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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 透過 Vertex AI 建構及部署機器學習解決方案 課程，即可瞭解如何使用 Google Cloud 的 Vertex AI 平台、AutoML 和自訂訓練服務， 訓練、評估、調整、解釋及部署機器學習模型。 這個技能徽章課程適合專業數據資料學家和機器學習 工程師，完成即可取得中階技能徽章。技能 徽章是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和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應用相關知識。完成這個技能徽章課程 和結業評量挑戰實驗室，就能獲得數位徽章， 並與親友分享。
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完成 建立 Google Cloud 網路 課程即可獲得技能徽章。這個課程將說明 部署及監控應用程式的多種方法，包括查看 IAM 角色及新增/移除 專案存取權、建立虛擬私有雲網路、部署及監控 Compute Engine VM、編寫 SQL 查詢、在 Compute Engine 部署及監控 VM，以及 使用 Kubernetes 透過多種方法部署應用程式。 「技能徽章」是 Google Cloud 核發的獨家數位徽章，用於肯定 您對 Google Cloud 產品和服務的精通程度，代表您已通過測驗， 能在互動式實作環境中應用相關知識。完成這個技能徽章課程和 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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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.
完成 在 Google Cloud 實作 DevOps 工作流程 技能徽章中階課程， 即可證明您具備下列技能：使用 Cloud Source Repositories 建立 Git 存放區、 在 Google Kubernetes Engine (GKE) 發布、管理和調度 Deployment， 以及建立 CI/CD 管道，自動建構容器映像檔與執行 GKE 部署作業。 「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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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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這堂課程可讓參加人員瞭解如何使用確實有效的設計模式，在 Google Cloud 中打造相當可靠且效率卓越的解決方案。這堂課程接續了「設定 Google Compute Engine 架構」或「設定 Google Kubernetes Engine 架構」課程的內容，並假設參加人員曾實際運用上述任一課程涵蓋的技術。這堂課程結合了簡報、設計活動和實作研究室，可讓參加人員瞭解如何定義業務和技術需求，並在兩者之間取得平衡，設計出相當可靠、可用性高、安全又符合成本效益的 Google Cloud 部署項目。
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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 從 BigQuery 資料取得深入分析結果 技能徽章入門課程，即可證明您具備下列技能： 撰寫 SQL 查詢、查詢公開資料表、將樣本資料載入 BigQuery、使用 BigQuery 的查詢驗證工具 排解常見語法錯誤，以及在 Looker Studio 中 透過連結 BigQuery 資料建立報表。 「技能徽章」是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和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。完成本技能徽章課程及結業評量挑戰 實驗室，即可取得技能徽章並與他人分享。
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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「運用 BigQuery ML 建立機器學習模型」技能徽章中階課程，即可證明您具備下列技能： 可使用 BigQuery ML 建立及評估機器學習模型，並根據資料進行預測。 「技能徽章」是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和服務方面的精熟技能， 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實驗室，即可取得技能徽章 並與他人分享。
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.
這堂隨選密集課程會向參加人員說明 Google Cloud 提供的全方位彈性基礎架構和平台服務，並將重點放在 Compute Engine。這堂課程結合了視訊講座、示範和實作研究室，可讓參加人員探索及部署解決方案元素，例如網路、系統和應用程式服務等基礎架構元件。另外，這堂課也會介紹如何部署實用的解決方案，包括客戶提供的加密金鑰、安全性和存取權管理機制、配額與帳單，以及資源監控功能。
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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.
In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
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只要修完「在 Google Cloud 設定應用程式開發環境」課程，就能獲得技能徽章。 在本課程中，您將學會如何使用以下技術的基本功能，建構和連結以儲存空間為中心的雲端基礎架構：Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。 「技能徽章」是 Google Cloud 核發的獨家數位徽章，用於表彰您相當熟悉 Google Cloud 產品與服務，並已通過測驗，能在互動式實作環境中應用相關知識。只要完成這個技能徽章課程和最終評量挑戰研究室，即可取得技能徽章並與親友分享成就。
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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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歡迎參加「開始使用 Google Kubernetes Engine」課程。Kubernetes 是位於應用程式和硬體基礎架構之間的軟體層。如果您對這項技術感興趣，這堂課程可以滿足您的需求。有了 Google Kubernetes Engine，您就能在 Google Cloud 中以代管服務的形式使用 Kubernetes。
本課程的目標在於介紹 Google Kubernetes Engine (常簡稱為 GKE) 的基本概念，以及如何將應用程式容器化，以便在 Google Cloud 中執行。課程首先會初步介紹 Google Cloud，隨後簡介容器、Kubernetes、Kubernetes 架構和 Kubernetes 作業。
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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 基礎知識：核心基礎架構」介紹了在使用 Google Cloud 時會遇到的重要概念和術語。本課程會透過影片和實作實驗室，介紹並比較 Google Cloud 的多種運算和儲存服務，同時提供重要的資源和政策管理工具。
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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
運用 Vertex AI 和 Flutter 打造生成式 AI 代理
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
運用 BigQuery 建立嵌入項目、向量搜尋和 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
機器學習運作 (MLOps) 與 Vertex AI：模型評估
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
開發人員的負責任 AI 技術：隱私權與安全性
Earned Jun 13, 2025 EDT
開發人員的負責任 AI 技術：可解釋性與透明度
Earned Jun 12, 2025 EDT
生成式 AI 適用的機器學習運作 (MLOps)
Earned Jun 12, 2025 EDT
建立圖像說明生成模型
Earned Jun 12, 2025 EDT
Transformer 和 BERT 模型
Earned Jun 12, 2025 EDT
編碼器-解碼器架構
Earned Jun 11, 2025 EDT
注意力機制
Earned Jun 11, 2025 EDT
圖像生成簡介
Earned Jun 11, 2025 EDT
大型語言模型簡介
Earned Jun 11, 2025 EDT
生成式 AI 簡介
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
透過 Agentspace 加速交流知識
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 實作 Cloud 安全防護措施：基礎知識
Earned Mar 13, 2025 EDT
Google Cloud 中的資料工程簡介
Earned Mar 5, 2025 EST
基本概念：基礎架構
Earned Mar 5, 2025 EST
Vector Search 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 建立安全的資料湖泊
Earned Oct 24, 2024 EDT
Monitoring in Google Cloud
Earned Oct 24, 2024 EDT
在 Vertex AI 使用 Gemini API 探索生成式 AI
Earned Oct 23, 2024 EDT
在 Google Cloud 儲存、處理與管理資料 - 控制台
Earned Oct 22, 2024 EDT
Use APIs to Work with Cloud Storage
Earned Oct 22, 2024 EDT
Google Cloud Compute 基本操作
Earned Oct 22, 2024 EDT
Tag and Discover BigLake Data
Earned Oct 21, 2024 EDT
以串流方式將分析資料傳入 BigQuery
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
開始使用 Pub/Sub
Earned Oct 16, 2024 EDT
開始使用 API Gateway
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 設計提示
Earned Jul 24, 2024 EDT
Generative AI Fundamentals
Earned Jul 22, 2024 EDT
Vertex AI Studio 簡介
Earned Jul 22, 2024 EDT
Google Cloud 的 AI 和機器學習服務簡介
Earned Jul 22, 2024 EDT
建構安全的 Google Cloud 網路
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 資料分析簡介
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 實作負載平衡功能
Earned May 13, 2024 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned Apr 26, 2024 EDT
Architecting with Google Kubernetes Engine: Foundations - 繁體中文
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 建構資料網格
Earned Feb 2, 2024 EST
開始使用 Dataplex
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
使用 Gemini：端對端 SDLC
Earned Jan 15, 2024 EST
使用 Gemini：DevOps 工程師
Earned Jan 15, 2024 EST
使用 Gemini：網路工程師
Earned Jan 15, 2024 EST
Achieving Advanced Insights with BigQuery
Earned Jan 15, 2024 EST
在 Google Cloud 為機器學習 API 準備資料
Earned Jan 11, 2024 EST
使用 BigQuery ML 為預測模型進行資料工程
Earned Jan 10, 2024 EST
使用 Gemini：數據資料學家和分析師
Earned Jan 10, 2024 EST
使用 Gemini：資安工程師
Earned Jan 10, 2024 EST
Gemini in Google Slides
Earned Jan 8, 2024 EST
使用 Gemini：應用程式開發人員
Earned Jan 8, 2024 EST
Gemini for Google Workspace 簡介
Earned Jan 8, 2024 EST
Gemini in Gmail
Earned Jan 8, 2024 EST
Gemini in Google Docs
Earned Jan 8, 2024 EST
Gemini in Google Sheets
Earned Jan 8, 2024 EST
使用 Gemini：雲端架構師
Earned Jan 8, 2024 EST
透過 BigQuery 建構資料倉儲
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
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則
Earned Dec 14, 2023 EST
負責任的 AI 技術簡介
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
透過 Vertex AI 建構及部署機器學習解決方案
Earned Jun 15, 2023 EDT
建立 Google Cloud 網路
Earned Jun 1, 2023 EDT
Certification Learning Path: Professional Cloud DevOps Engineer
Earned May 30, 2023 EDT
透過 Google Cloud Observability 監控及記錄系統狀態
Earned May 29, 2023 EDT
在 Google Cloud 實作 DevOps 工作流程
Earned May 26, 2023 EDT
DEPRECATED Cloud Operations and Service Mesh with Anthos
Earned May 25, 2023 EDT
可靠的 Google Cloud 基礎架構：設計與程序
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
從 BigQuery 資料取得深入分析結果
Earned Feb 9, 2023 EST
Launching into Machine Learning
Earned Feb 9, 2023 EST
運用 BigQuery ML 建立機器學習模型
Earned Jan 27, 2023 EST
為 Looker 資訊主頁和報表準備資料
Earned Jan 27, 2023 EST
Applying Machine Learning to your Data with Google Cloud
Earned Jan 26, 2023 EST
使用 BigQuery 進行機器學習
Earned Jan 25, 2023 EST
重要的 Google Cloud 基礎架構：核心服務
Earned Nov 22, 2022 EST
Getting Started with Terraform for Google Cloud
Earned Nov 21, 2022 EST
在 Google Cloud 使用 Terraform 建構基礎架構
Earned Oct 4, 2022 EDT
在 Compute Engine 實作負載平衡功能
Earned Oct 3, 2022 EDT
Google Cloud Essentials
Earned Oct 3, 2022 EDT
在 Google Cloud 設定應用程式開發環境
Earned Aug 5, 2022 EDT
Scaling with Google Cloud Operations
Earned Aug 4, 2022 EDT
開始使用 Google Kubernetes Engine
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 基礎知識：核心基礎架構
Earned Jul 19, 2022 EDT
Digital Transformation with Google Cloud
Earned Jul 11, 2022 EDT