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在 Google Cloud 控制台中运用您的技能

Thanh Hoàng Lê Cát

成为会员时间：2024

钻石联赛

17081 积分
Get Started with Sensitive Data Protection Earned Oct 5, 2025 EDT
Secure Software Delivery Earned Oct 5, 2025 EDT
使用 Gemini 多模態功能和多模態 RAG 檢查複合型文件 Earned Oct 4, 2025 EDT
在 Vertex AI 使用 Gemini API 探索生成式 AI Earned Oct 2, 2025 EDT
使用 Gemini 和 Streamlit 開發生成式 AI 應用程式 Earned Oct 2, 2025 EDT
Build Custom Processors with Document AI Earned Oct 1, 2025 EDT
Use Machine Learning APIs on Google Cloud Earned Oct 1, 2025 EDT
Automate Data Capture at Scale with Document AI Earned Oct 1, 2025 EDT
在 Google Cloud 為機器學習 API 準備資料 Earned Sep 28, 2025 EDT
Cloud Speech API：3 種應用 Earned Sep 28, 2025 EDT
運用 BigQuery 導入多模態向量搜尋 Earned Sep 28, 2025 EDT
運用 Gemini 分析多模態資料並推論 Earned Sep 23, 2025 EDT
強化 Gemini 模型功能 Earned Sep 23, 2025 EDT
Gemini 和 Imagen 實務應用：建構 AI 應用程式 Earned Sep 22, 2025 EDT
在 Vertex AI 設計提示 Earned Sep 22, 2025 EDT
Create and Manage AlloyDB Instances Earned Apr 18, 2024 EDT
Managing Machine Learning Projects with Google Cloud Earned Apr 16, 2024 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Earned Apr 15, 2024 EDT
Perform Predictive Data Analysis in BigQuery Earned Apr 13, 2024 EDT
Analyze Sentiment with Natural Language API Earned Apr 13, 2024 EDT
Analyze Images with the Cloud Vision API Earned Apr 11, 2024 EDT
Analyze Speech and Language with Google APIs Earned Apr 11, 2024 EDT
Detect Manufacturing Defects Using Visual Inspection AI Earned Apr 9, 2024 EDT
Intro to ML: Image Processing Earned Apr 8, 2024 EDT
Build LookML Objects in Looker Earned Apr 3, 2024 EDT
Classify Images with TensorFlow on Google Cloud Earned Apr 1, 2024 EDT
機器學習簡介：語言處理 Earned Mar 28, 2024 EDT
基本概念：資料、機器學習和 AI Earned Mar 26, 2024 EDT
探索生成式 AI - Vertex AI Earned Mar 22, 2024 EDT

Complete the introductory Get Started with Sensitive Data Protection skill badge course to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention API) to inspect, redact, and de-identify sensitive data in Google Cloud.

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Complete the intermediate Secure Software Delivery skill badge to demonstrate your proficiency in proactively integrating security into the software development lifecycle (SDLC) with DevSecOps principles. You'll learn how to utilize Google Kubernetes Engine (GKE) and Cloud Run for secure container image deployment, implement automated vulnerability scanning to proactively identify risks, and streamline application development with Artifact Registry while maintaining a focus on security. Additionally, you'll gain skills in integrating Cloud Build for robust development processes and implementing Admission Control Policies for fine-grained control over your environment.

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完成 使用 Gemini 多模態功能和多模態 RAG 檢查複合型文件 技能徽章中階課程，即可證明您具備下列技能： 透過 Gemini 多模態功能，使用多模態提示從文字和影像資料擷取資訊、生成影片說明，以及擷取影片以外的額外資訊； 透過 Gemini 的多模態檢索增強生成 (RAG) 功能，為含有文字和圖片的文件建構中繼資料、取得所有相關文字分塊，以及顯示引用資料。 「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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完成「在 Vertex AI 使用 Gemini API 探索生成式 AI」技能徽章中階課程，即可證明自己具備下列技能： 可運用 Gemini API 生成文字、分析圖片和影片來強化內容創作能力，還能使用函式呼叫技巧。 本課程將帶您瞭解如何善用進階的 Gemini 技術、使用多模態內容生成功能，並提升 AI 專案的潛力。

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完成 使用 Gemini 和 Streamlit 開發生成式 AI 應用程式 技能徽章中階課程，即可證明您具備下列技能： 生成文字、透過 Python SDK 和 Gemini API 呼叫函式，以及運用 Cloud Run 部署 Streamlit 應用程式。 您將瞭解如何以不同方式透過提示請 Gemini 生成文字、使用 Cloud Shell 測試及疊代 Streamlit 應用程式，隨後封裝成 Docker 容器並在 Cloud Run 中部署。

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Earn a skill badge by completing the Build Custom Processors with Document AI course. You learn how to extract data and classify documents by creating custom ML models specific to your business needs. This course teaches the foundation skills of building your own processors, working with optical character recognition, form parsing, processor creation, and uptraining the DocumentAI model.

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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.

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Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.

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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。

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完成「Cloud Speech API：3 種應用」課程，瞭解如何使用語音相關 API 工具合成及轉錄語音， 即可獲得入門級技能徽章。

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完成運用 BigQuery 導入多模態向量搜尋技能徽章中階課程， 即可證明自己具備下列技能：使用 Gemini in BigQuery 生成 SQL 程式碼並偵錯、執行情緒分析、 總結文字重點並找出關鍵字、生成嵌入項目、建立檢索增強生成 (RAG) pipeline， 以及導入多模態向量搜尋。 技能徽章是 Google Cloud 獨家核發的數位徽章， 用於肯定您對 Google Cloud 產品和服務的精通程度。 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，以及挑戰實驗室的結業評量之後， 即可取得數位徽章並與他人分享。

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完成運用 Gemini 分析多模態資料並推論技能徽章中階課程，即可證明自己具備下列技能：使用 Gemini 2.0 Flash 分析文字、圖像、音訊 (以樂譜呈現) 和影片資料；以及依據這類複合型資訊，推導出結論及擷取洞察結果。 「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 這個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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完成強化 Gemini 模型功能技能徽章中階課程，即可證明自己具備下列技能：運用 Gemini 模型的進階功能 (包括生成及執行程式碼、建立基準、生成受控內容、建立合成資料等)，打造更強大且精密的 AI 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 這個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「Gemini 和 Imagen 實務應用：建構 AI 應用程式」技能徽章入門課程，即可證明您具備下列技能：圖片辨識、自然語言處理、 使用 Google 強大的 Gemini 和 Imagen 模型生成圖片，以及在 Vertex AI 平台上部署應用程式。

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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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Complete the introductory Create and Manage AlloyDB Instances skill badge to demonstrate skills in the following: performing core AlloyDB operations and tasks, migrating to AlloyDB from PostgreSQL, administering an AlloyDB database, and accelerating analytical queries using the AlloyDB Columnar Engine.

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Business professionals in non-technical roles have a unique opportunity to lead or influence machine learning projects. If you have questions about machine learning and want to understand how to use it, without the technical jargon, this course is for you. Learn how to translate business problems into machine learning use cases and vet them for feasibility and impact. Find out how you can discover unexpected use cases, recognize the phases of an ML project and considerations within each, and gain confidence to propose a custom ML use case to your team or leadership or translate the requirements to a technical team.

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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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Complete the intermediate Perform Predictive Data Analysis in BigQuery skill badge course to demonstrate skills in the following: creating datasets in BigQuery by importing CSV and JSON files; harnessing the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on soccer event data and evaluate the impressiveness of World Cup goals.

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Earn a skill badge by completing the Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.

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Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.

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Earn a skill badge by completing the Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.

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Earn a skill badge by completing the Detect Manufacturing Defects using Visual Inspection AI course, where you learn how to use Visual Inspection AI to deploy a solution artifact and test that it can successfully identify defects in a manufacturing process.

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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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Complete the introductory Build LookML Objects in Looker skill badge course 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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Earn the intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.

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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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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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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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