DEPRECATED Build LangChain Applications using Vertex AI
Earned Apr 9, 2024 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned Mar 2, 2024 EST
Gemini for Google Workspace 簡介
Earned Feb 1, 2024 EST
Preparing for Your Professional Cloud Network Engineer Journey
Earned Jan 31, 2024 EST
使用 Gemini：雲端架構師
Earned Jan 27, 2024 EST
Trust and Security with Google Cloud
Earned Jan 25, 2024 EST
Innovating with Google Cloud Artificial Intelligence
Earned Jan 25, 2024 EST
開始使用 Eventarc
Earned Jan 24, 2024 EST
Enterprise Search on Generative AI App Builder
Earned Jan 23, 2024 EST
機器學習簡介：語言處理
Earned Jan 18, 2024 EST
Serverless Data Processing with Dataflow: Foundations
Earned Jan 11, 2024 EST
Exploring Data Transformation with Google Cloud - Locales
Earned Jan 8, 2024 EST
Google Cloud 的 AI 和機器學習服務簡介
Earned Jan 5, 2024 EST
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned Jan 5, 2024 EST
Google Cloud 運算的基本概念：Cloud 運算基礎知識
Earned Jan 4, 2024 EST
基本概念：資料、機器學習和 AI
Earned Dec 18, 2023 EST
Developing Containerized Applications on Google Cloud
Earned Nov 10, 2023 EST
Logging and Monitoring in Google Cloud
Earned Nov 1, 2023 EDT
Architecting with Google Kubernetes Engine: Production
Earned Oct 31, 2023 EDT
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則
Earned Sep 28, 2023 EDT
Launching into Machine Learning
Earned Sep 22, 2023 EDT
Innovating with Data and Google Cloud
Earned Jul 20, 2023 EDT
Creating Infrastructure on Google Cloud with Terraform
Earned Jul 20, 2023 EDT
Generative AI Fundamentals - 繁體中文
Earned Jul 19, 2023 EDT
使用 Cloud Run 函式建構無伺服器應用程式
Earned Jul 19, 2023 EDT
DEPRECATED BigQuery for Data Warehousing
Earned Jul 12, 2023 EDT
Machine Learning APIs
Earned Jul 10, 2023 EDT
彈性的 Google Cloud 基礎架構：資源調度與自動化
Earned Jun 10, 2023 EDT
Baseline: Deploy & Develop
Earned Jun 7, 2023 EDT
探索生成式 AI - Vertex AI
Earned Jun 5, 2023 EDT
Vertex AI Studio 簡介
Earned Jun 5, 2023 EDT
負責任的 AI 技術簡介
Earned Jun 5, 2023 EDT
DevOps Essentials
Earned May 26, 2023 EDT
建立圖像說明生成模型
Earned May 25, 2023 EDT
圖像生成簡介
Earned May 24, 2023 EDT
編碼器-解碼器架構
Earned May 24, 2023 EDT
Transformer 和 BERT 模型
Earned May 24, 2023 EDT
注意力機制
Earned May 24, 2023 EDT
大型語言模型簡介
Earned May 24, 2023 EDT
Google Cloud 中的 Kubernetes
Earned May 18, 2023 EDT
重要的 Google Cloud 基礎架構：核心服務
Earned May 16, 2023 EDT
基本概念：基礎架構
Earned May 16, 2023 EDT
生成式 AI 簡介
Earned May 11, 2023 EDT
Machine Learning Operations (MLOps): Getting Started
Earned May 10, 2023 EDT
重要的 Google Cloud 基礎架構：基本概念
Earned May 9, 2023 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned May 9, 2023 EDT
DEPRECATED Cloud Architecture
Earned May 7, 2023 EDT
Architecting with Google Kubernetes Engine: Foundations - 繁體中文
Earned Apr 24, 2023 EDT
在 Google Cloud 設定應用程式開發環境
Earned Apr 4, 2023 EDT
開始使用 Google Kubernetes Engine
Earned Mar 29, 2023 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned Mar 19, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Mar 19, 2023 EDT
Google Cloud 基礎知識：核心基礎架構
Earned Mar 3, 2023 EST
Google Cloud 必備知識
Earned Mar 3, 2023 EST
雲端工程
Earned Feb 28, 2023 EST
Getting Started with Terraform for Google Cloud
Earned Feb 17, 2023 EST
Scaling with Google Cloud Operations
Earned Jan 23, 2023 EST
Modernize Infrastructure and Applications with Google Cloud
Earned Jan 23, 2023 EST
Exploring Data Transformation with Google Cloud
Earned Jan 18, 2023 EST
Digital Transformation with Google Cloud
Earned Jan 18, 2023 EST
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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Welcome to Observability in Google Cloud, the second part of a two-part course series. It is suggested that you complete part 1, Logging and Monitoring in Google Cloud, prior to taking this course.
This course is all about application performance management tools, including Error Reporting, Cloud Trace, and Cloud Profiler.
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This course helps learners prepare for the Professional Cloud Security Engineer (PCSE) Certification exam. Learners will be exposed to and engage with exam topics through a series of lectures, diagnostic questions, and knowledge checks. After completing this course, learners will have a personalized workbook that will guide them through the rest of their certification readiness journey.
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This course introduces you to event-based applications and teaches you how to use service orchestration and choreography to coordinate microservices. Using lectures and hands-on labs, you learn how to use Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler to build microservices applications on Google Cloud.
Explore the fundamentals of Flutter application development in this hands-on quest! Within this quest, you will build a "Hello World" Flutter application, design a frontend for a shopping application, and learn how to connect your Flutter applications to backend services. Each lab in this quest utilizes a pre-provisioned development environment allowing minimal setup to get into the application code!
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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。
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這個簡短的課程會說明如何在 Google Cloud 整合應用程式與 Gemini 1.0 Pro 模型，讓您瞭解 Gemini API 及其生成式 AI 模型，並學習如何透過程式碼存取 Gemini 1.0 Pro 和 Gemini 1.0 Pro Vision 模型。另外，您會在應用程式中使用文字、圖片和影片提示，測試模型的功能。
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Introduction to Cloud Identity serves as the starting place for any new Cloud Identity, Identity/Access Management/Mobile Device Management admins as they begin their journey of managing and establishing security and access management best practices for their organization. This 15-30 hour accelerated, one-week course will leave you feeling confident to utilize the basic functions of the Admin Console to manage users, control access to services, configure common security settings, and much more. Through a series of introductory lessons, step-by-step hands-on exercises, Google knowledge resources, and knowledge checks, learners can expect to leave this training with all of the skills they need to get started as new Cloud Identity Administrators.
In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.
This course introduces the Cloud Run serverless platform for running applications.
In this course, you learn about the fundamentals of Cloud Run, its resource model and the container lifecycle.
You learn about service identities, how to control access to services, and how to develop and test your
application locally before deploying it to Cloud Run. The course also teaches you how to integrate
with other services on Google Cloud so you can build full-featured applications.
完成「在 Google Cloud 使用 Terraform 建構基礎架構」技能徽章中階課程， 即可證明自己具備下列知識與技能：使用 Terraform 的基礎架構即程式碼 (IaC) 原則、運用 Terraform 設定佈建及管理 Google Cloud 資源、有效管理狀態 (本機和遠端)，以及將 Terraform 程式碼模組化，以利重複使用和管理。
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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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Complete the introductory Build LangChain Applications using Vertex AI skill badge to learn how to build Generative AI applications using LangChain and the Retrieval Augmented Generation (RAG) technique for text-based content, powered by Vertex AI's advanced Generative AI capabilities. Discover how to integrate powerful large language models (LLMs) with search and retrieval workflows, boosting the accuracy and relevance of your generated content. Earn a Google Cloud skill badge and showcase your expertise by completing the course and its final assessment challenge lab.
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TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.
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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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This course helps you structure your preparation for the Professional 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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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。
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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.
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 Generative AI App Builder to integrate enterprise-grade generative AI search.
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大家都知道，機器學習是發展最快的科技領域之一， 而 Google Cloud Platform 在這方面功不可沒。 GCP 提供多種 API，凡是與機器學習相關的任務，幾乎都能處理。您將在本入門課程的 實驗室，實際演練機器學習技術 在語言處理方面的應用，學會如何從文中擷取實體資訊、 執行情緒和語法分析，並使用 Speech-to-Text API 轉錄語音。
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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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This course, Exploring Data Transformation with Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Exploring Data Transformation with Google Cloud.
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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本課程介紹 Google Cloud 的 AI 和機器學習 (ML) 功能，著重說明如何開發生成式和預測式 AI 專案。我們也會探討「從資料到 AI」整個生命週期都適用的技術、產品和工具，並透過互動式練習，協助資料科學家、AI 開發人員和機器學習工程師精進專業知識。
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production.
Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.
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Google Cloud 運算基本概念課程，適合幾乎沒有雲端運算背景或經驗的學員。這些課程會說明雲端運算基本知識、大數據和機器學習的核心概念，以及 Google Cloud 的角色和定位。完成這一系列課程後，學員將能夠闡述這些概念並展示實用技能。學員應依以下順序完成課程：
1. Google Cloud 運算的基本概念：Cloud 運算基礎知識
2. Google Cloud 運算的基本概念：Google Cloud 基礎架構
3. Google Cloud 運算的基本概念：Google Cloud 的網路與安全性
4. Google Cloud 運算的基本概念：Google Cloud 中的資料、機器學習和 AI
第一門課會概略說明雲端運算、Google Cloud 的使用方式，以及不同的運算選項。
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大數據、機器學習和人工智慧 (AI) 是時下熱門的 電腦相關話題，但這些領域相當專業，就算想要入門 也難以取得教材或資料。幸好，Google Cloud 提供了此領域的多種服務，而且容易使用。 參加這堂入門課程，您就能踏出第一步， 開始學習運用 BigQuery、Cloud Speech API 以及 Video Intelligence 等工具。
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In this course, you learn about containers and how to build, and package container images. The content in this course includes best practices for creating and securing containers, and provides an introduction to Cloud Run and Google Kubernetes Engine for application developers.
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Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.
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In this course, you'll learn about Kubernetes and Google Kubernetes Engine (GKE) security; logging and monitoring; and using Google Cloud managed storage and database services from within GKE.
This is the second course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Reliable Google Cloud Infrastructure: Design and Process course or the Hybrid Cloud Infrastructure Foundations with Anthos course.
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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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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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Cloud technology on its own only provides a fraction of the true value to a business; When combined with data–lots and lots of it–it has the power to truly unlock value and create new experiences for customers.
In this course, you'll learn what data is, historical ways companies have used it to make decisions, and why it is so critical for machine learning. This course also introduces learners to technical concepts such as structured and unstructured data. database, data warehouse, and data lakes. It then covers the most common and fastest growing Google Cloud products around data.
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In this quest you will get hands-on experience writing infrastructure as code with Terraform.
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完成「Introduction to Generative AI」、「Introduction to Large Language Models」和「Introduction to Responsible AI」課程，即可獲得技能徽章。通過最終測驗，就能展現您對生成式 AI 基本概念的掌握程度。
「技能徽章」是 Google Cloud 核發的數位徽章，用於表彰您對 Google Cloud 產品和服務的相關知識。您可以將技能徽章公布在社群媒體的個人資料中，向其他人分享您的成果。
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若想獲得入門技能徽章，請完成「使用 Cloud Run 函式建構無伺服器應用程式」課程， 瞭解如何在 Google Cloud 控制台和指令列中 使用 Cloud Run functions。
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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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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? 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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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。這堂課結合了視訊講座、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，包括安全地建立互連網路、負載平衡、自動調度資源、基礎架構自動化，以及代管服務。
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In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.
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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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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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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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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this course you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out!
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。
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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Kubernetes 是最受歡迎的容器自動化調度管理系統，Google Kubernetes Engine 則專門支援 Google Cloud 中的 代管 Kubernetes 部署項目。這門進階課程將帶您實際練習設定 Docker 映像檔和容器，並部署完整的 Kubernetes Engine 應用程式。 您會學到如何將容器自動化調度管理機制， 整合到自己的工作流程，這些技巧相當實用。 想透過實作挑戰實驗室展現 技能、驗收學習成果嗎？本課程結束後，再完成 在 Google Cloud 部署 Kubernetes 應用程式課程 結尾的挑戰實驗室，即可獲得專屬 Google Cloud 數位徽章。
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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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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 introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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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，尤其側重於 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、虛擬機器和應用程式服務等基礎架構元件。您會瞭解如何透過控制台和 Cloud Shell 使用 Google Cloud。另外，您也能瞭解雲端架構師的職責、基礎架構設計方法，以及具備虛擬私有雲 (VPC)、專案、網路、子網路、IP 位址、路徑和防火牆規則的虛擬網路設定。
This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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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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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。
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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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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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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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「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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在這堂入門課程，您將實際練習使用 Google Cloud 的基礎工具和服務。本課程包含可選擇觀賞的影片， 針對實驗室涵蓋的概念提供更多背景資訊，協助您複習。「Google Cloud 必備知識」 是適合 Google Cloud 學員的第一堂課， 即使您尚未學習或不熟悉雲端知識， 也能從這堂課獲得實務經驗，並應用於第一項 Google Cloud 專案。不管是撰寫 Cloud Shell 指令 和部署第一部虛擬機器，還是在 Kubernetes Engine 或透過負載平衡執行應用程式， 「Google Cloud 必備知識」都是認識平台基本功能的最佳入門資源。
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本入門課程有別於其他課程。 透過這些實驗室，IT 專業人員將有機會實際練習， 熟悉出現在 Google Cloud 助理雲端工程師認證中的主題和服務。本課程包含多個專門的實驗室，從 IAM、網路建立 到 Kubernetes Engine 部署作業， 可全面驗收您的 Google Cloud 知識。請注意，雖然進行這些 實驗室可提升您的技能和能力，但仍建議同時詳閱 測驗指南和其他可用的準備資源。
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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.
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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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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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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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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.
Preparing for your Professional Cloud Architect Journey
Earned Jun 13, 2024 EDT
Observability in Google Cloud
Earned Jun 13, 2024 EDT
Preparing for Your Professional Cloud Security Engineer Journey
Earned Jun 11, 2024 EDT
Service Orchestration and Choreography on Google Cloud
Earned Jun 10, 2024 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned Jun 1, 2024 EDT
Flutter Development
Earned May 29, 2024 EDT
在 Vertex AI 設計提示
Earned May 13, 2024 EDT
在 Google Cloud 整合應用程式與 Gemini 1.0 Pro
Earned May 6, 2024 EDT
Introduction to Cloud Identity
Earned Apr 30, 2024 EDT
充實中繼資料及發掘 BigLake 資料
Earned Apr 25, 2024 EDT
Managing Cloud Infrastructure with Terraform
Earned Apr 24, 2024 EDT
建立 Google Cloud 網路
Earned Apr 17, 2024 EDT
Developing Applications with Cloud Run on Google Cloud: Fundamentals
Earned Apr 15, 2024 EDT
在 Compute Engine 導入 Cloud Load Balancing
Earned Apr 15, 2024 EDT
在 Google Cloud 使用 Terraform 建構基礎架構
Earned Apr 12, 2024 EDT
使用 Gemini：應用程式開發人員
Earned Apr 10, 2024 EDT
DEPRECATED Build LangChain Applications using Vertex AI
Earned Apr 9, 2024 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned Mar 2, 2024 EST
Gemini for Google Workspace 簡介
Earned Feb 1, 2024 EST
Preparing for Your Professional Cloud Network Engineer Journey
Earned Jan 31, 2024 EST
使用 Gemini：雲端架構師
Earned Jan 27, 2024 EST
Trust and Security with Google Cloud
Earned Jan 25, 2024 EST
Innovating with Google Cloud Artificial Intelligence
Earned Jan 25, 2024 EST
開始使用 Eventarc
Earned Jan 24, 2024 EST
Enterprise Search on Generative AI App Builder
Earned Jan 23, 2024 EST
機器學習簡介：語言處理
Earned Jan 18, 2024 EST
Serverless Data Processing with Dataflow: Foundations
Earned Jan 11, 2024 EST
Exploring Data Transformation with Google Cloud - Locales
Earned Jan 8, 2024 EST
Google Cloud 的 AI 和機器學習服務簡介
Earned Jan 5, 2024 EST
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned Jan 5, 2024 EST
Google Cloud 運算的基本概念：Cloud 運算基礎知識
Earned Jan 4, 2024 EST
基本概念：資料、機器學習和 AI
Earned Dec 18, 2023 EST
Developing Containerized Applications on Google Cloud
Earned Nov 10, 2023 EST
Logging and Monitoring in Google Cloud
Earned Nov 1, 2023 EDT
Architecting with Google Kubernetes Engine: Production
Earned Oct 31, 2023 EDT
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則
Earned Sep 28, 2023 EDT
Launching into Machine Learning
Earned Sep 22, 2023 EDT
Innovating with Data and Google Cloud
Earned Jul 20, 2023 EDT
Creating Infrastructure on Google Cloud with Terraform
Earned Jul 20, 2023 EDT
Generative AI Fundamentals - 繁體中文
Earned Jul 19, 2023 EDT
使用 Cloud Run 函式建構無伺服器應用程式
Earned Jul 19, 2023 EDT
DEPRECATED BigQuery for Data Warehousing
Earned Jul 12, 2023 EDT
Machine Learning APIs
Earned Jul 10, 2023 EDT
彈性的 Google Cloud 基礎架構：資源調度與自動化
Earned Jun 10, 2023 EDT
Baseline: Deploy & Develop
Earned Jun 7, 2023 EDT
探索生成式 AI - Vertex AI
Earned Jun 5, 2023 EDT
Vertex AI Studio 簡介
Earned Jun 5, 2023 EDT
負責任的 AI 技術簡介
Earned Jun 5, 2023 EDT
DevOps Essentials
Earned May 26, 2023 EDT
建立圖像說明生成模型
Earned May 25, 2023 EDT
圖像生成簡介
Earned May 24, 2023 EDT
編碼器-解碼器架構
Earned May 24, 2023 EDT
Transformer 和 BERT 模型
Earned May 24, 2023 EDT
注意力機制
Earned May 24, 2023 EDT
大型語言模型簡介
Earned May 24, 2023 EDT
Google Cloud 中的 Kubernetes
Earned May 18, 2023 EDT
重要的 Google Cloud 基礎架構：核心服務
Earned May 16, 2023 EDT
基本概念：基礎架構
Earned May 16, 2023 EDT
生成式 AI 簡介
Earned May 11, 2023 EDT
Machine Learning Operations (MLOps): Getting Started
Earned May 10, 2023 EDT
重要的 Google Cloud 基礎架構：基本概念
Earned May 9, 2023 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned May 9, 2023 EDT
DEPRECATED Cloud Architecture
Earned May 7, 2023 EDT
Architecting with Google Kubernetes Engine: Foundations - 繁體中文
Earned Apr 24, 2023 EDT
在 Google Cloud 設定應用程式開發環境
Earned Apr 4, 2023 EDT
開始使用 Google Kubernetes Engine
Earned Mar 29, 2023 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned Mar 19, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Mar 19, 2023 EDT
Google Cloud 基礎知識：核心基礎架構
Earned Mar 3, 2023 EST
Google Cloud 必備知識
Earned Mar 3, 2023 EST
雲端工程
Earned Feb 28, 2023 EST
Getting Started with Terraform for Google Cloud
Earned Feb 17, 2023 EST
Scaling with Google Cloud Operations
Earned Jan 23, 2023 EST
Modernize Infrastructure and Applications with Google Cloud
Earned Jan 23, 2023 EST
Exploring Data Transformation with Google Cloud
Earned Jan 18, 2023 EST
Digital Transformation with Google Cloud
Earned Jan 18, 2023 EST