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。
這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。
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這是一堂入門級的微學習課程，旨在探討大型語言模型 (LLM) 的定義和用途，並說明如何調整提示來提高 LLM 成效。此外，也會介紹多項 Google 工具，協助您自行開發生成式 AI 應用程式。
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Description: According to IDC, by 2026, 7 PB of data will be generated per second globally. But what you *do* with the data is what matters. Data is the heart of digital transformation and offers incredible opportunities for organizations to accelerate the most strategic business outcomes, like revenue and productivity. Want to grow your skills and take advantage of the opportunity? Play now to get hands-on experience with Google Cloud's powerful data tools. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential.
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完成「在連結試算表中分析 BigQuery 資料」技能徽章，即可證明您能使用連結試算表，在 Google 試算表中存取、分析及共用數十億列的 BigQuery 資料，還能以圖表呈現。
More than 90% of IT leaders say they're looking to grow their cloud environments in the next several years, yet more than 80% of those same leaders identified a lack of skills as a barrier to growth. This means that tech skills (particularly cloud skills!) are in high demand. Want to grow your skills and take advantage of the opportunity? Play now to get hands-on experience with Google Cloud. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential. No experience required.
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完成「監控及管理 Google Cloud 資源」技能徽章入門課程，即可證明您具備下列技能：授予及撤銷 IAM 權限； 安裝 Monitoring 和 Logging 代理程式；建立、部署及測試事件導向的 Cloud Run 函式。
完成「在 Google Cloud 使用機器學習 API」課程，即可獲得進階技能徽章。本課程說明以下機器學習和 AI 技術的基本功能： Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。
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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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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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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.
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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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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
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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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Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.
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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.
Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. 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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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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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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完成「設定 Google Cloud 網路」課程，即可獲得技能徽章。 您將瞭解如何在 Google Cloud Platform 執行基本的網路工作，包括建立自訂網路、新增子網路防火牆規則，還有建立 VM 並測試 VM 之間的通訊延遲。
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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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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。
負責任的 AI 技術簡介
Earned Aug 3, 2023 EDT
編碼器-解碼器架構
Earned May 22, 2023 EDT
建立圖像說明生成模型
Earned May 22, 2023 EDT
圖像生成簡介
Earned May 21, 2023 EDT
Transformer 和 BERT 模型
Earned May 21, 2023 EDT
注意力機制
Earned May 19, 2023 EDT
生成式 AI 簡介
Earned May 19, 2023 EDT
大型語言模型簡介
Earned May 14, 2023 EDT
Level 2: Data Exploration with Looker, BigQuery and Sheets
Earned May 9, 2023 EDT
在連結試算表中分析 BigQuery 資料
Earned May 9, 2023 EDT
在 Google Cloud 儲存、處理與管理資料 - 控制台
Earned May 9, 2023 EDT
Level 1: Managing Resources and Data in the Cloud
Earned May 9, 2023 EDT
監控及管理 Google Cloud 資源
Earned May 8, 2023 EDT
為 Looker 資訊主頁和報表準備資料
Earned Nov 13, 2021 EST
在 Google Cloud 使用機器學習 API
Earned Nov 13, 2021 EST
Understanding LookML in Looker
Earned Nov 13, 2021 EST
Machine Learning APIs
Earned Nov 12, 2021 EST
Intro to ML: Image Processing
Earned Nov 12, 2021 EST
機器學習簡介：語言處理
Earned Nov 12, 2021 EST
NCAA® March Madness®: Bracketology with Google Cloud
Earned Nov 12, 2021 EST
基本概念：資料、機器學習和 AI
Earned Nov 11, 2021 EST
Cloud SQL
Earned Nov 10, 2021 EST
DEPRECATED BigQuery for Data Warehousing
Earned Nov 8, 2021 EST
透過 BigQuery 建構資料倉儲
Earned Nov 8, 2021 EST
從 BigQuery 資料取得深入分析結果
Earned Nov 8, 2021 EST
DEPRECATED BigQuery for Marketing Analysts
Earned Nov 7, 2021 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned Nov 7, 2021 EDT
Google Cloud 中的 Kubernetes
Earned Sep 23, 2021 EDT
設定 Google Cloud 網路
Earned Sep 22, 2021 EDT
DEPRECATED Cloud Architecture
Earned Sep 19, 2021 EDT
Google Cloud 必備知識
Earned Jul 1, 2021 EDT
在 Google Cloud 設定應用程式開發環境
Earned Jun 3, 2021 EDT
在 Compute Engine 導入 Cloud Load Balancing
Earned Jun 3, 2021 EDT