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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
使用多模态 Gemini 和多模态 RAG 检查富文档 Earned Oct 4, 2025 EDT
使用 Vertex AI 中的 Gemini API 探索生成式 AI Earned Oct 2, 2025 EDT
使用 Gemini 和 Streamlit 开发生成式 AI 应用 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 上为机器学习 API 准备数据 Earned Sep 28, 2025 EDT
Cloud Speech API：3 种使用方式 Earned Sep 28, 2025 EDT
使用 BigQuery 实现多模态向量搜索 Earned Sep 28, 2025 EDT
使用 Gemini 分析和推理多模态数据 Earned Sep 23, 2025 EDT
提升 Gemini 模型的能力 Earned Sep 23, 2025 EDT
使用 Gemini 和 Imagen 构建实用 AI 应用 Earned Sep 22, 2025 EDT
在 Vertex AI 中设计提示 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
机器学习简介：语言处理 Earned Mar 28, 2024 EDT
基准：数据、机器学习和 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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完成中级技能徽章课程使用多模态 Gemini 和多模态 RAG 检查富文档，展示您在以下方面的技能： 将多模态与 Gemini 配合使用，从而使用多模态提示从文本数据和视觉数据中提取信息、生成视频说明、 检索视频中不包含的额外信息； 将多模态检索增强生成 (RAG) 与 Gemini 配合使用，以构建包含文本和图片的文档的元数据、获取所有相关文本块并输出引用。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度； 您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛， 获得技能徽章， 在您的人际圈中炫出自己的技能。

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完成中级技能徽章课程使用 Vertex AI 中的 Gemini API 探索生成式 AI，展示自己在以下方面的技能： 文本生成技能、用于增强内容创作能力的图像和视频分析技能，以及在 Gemini API 中应用函数调用技术的技能。 了解如何运用先进的 Gemini 技术、探索多模态内容生成方法，并扩展 AI 赋能项目的功能。

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完成中级技能徽章课程“使用 Gemini 和 Streamlit 开发生成式 AI 应用”，展示您在以下方面的技能： 文本生成、通过 Python SDK 和 Gemini API 应用函数调用，以及通过 Cloud Run 部署 Streamlit 应用。 您将了解如何以不同方式通过提示来让 Gemini 生成文本、使用 Cloud Shell 进行测试，以及如何迭代 Streamlit 应用，随后将其封装成 Docker 容器并部署在 Cloud Run 中。

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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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完成入门级技能徽章课程在 Google Cloud 上为机器学习 API 准备数据，展示以下技能： 使用 Dataprep by Trifacta 清理数据、在 Dataflow 中运行数据流水线、在 Dataproc 中创建集群和运行 Apache Spark 作业，以及调用机器学习 API，包括 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。

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完成 Cloud Speech API：3 种使用方式课程，赢取入门级技能徽章。 在本课程中，您将了解如何使用语音相关 API 工具来合成和转写语音。

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完成中级技能徽章课程“使用 BigQuery 实现多模态向量搜索”， 展示自己在以下方面的技能：使用 Gemini in BigQuery 生成和调试 SQL；进行情感分析； 总结文本和识别关键字；生成嵌入；创建 RAG（检索增强生成）流水线； 以及实现多模态向量搜索。 技能徽章是由 Google Cloud 颁发的专属数字徽章， 旨在认可您在 Google Cloud 产品与服务方面的熟练度。 您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。 完成此技能徽章课程和作为最终评估的实验室挑战赛， 即可获得数字徽章，在您的人际圈中秀出自己的技能。

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完成中级技能徽章课程使用 Gemini 分析和推理多模态数据，展示自己在以下方面的技能：使用 Gemini 2.0 Flash 分析文本、图片、音频（以乐谱形式表示）和视频数据，对这些综合信息进行推理，以便得出结论并提取分析洞见。 技能徽章 是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛，获得技能徽章， 在您的人际圈中炫出自己的技能。

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完成中级技能徽章课程「提升 Gemini 模型的能力」，展示您在以下方面的技能: 利用 Gemini 模型的高级功能（包括代码生成和执行、接地、受控内容生成和合成数据创建）来构建功能更强大、更复杂的 AI 应用。 技能徽章 是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛，获得技能徽章， 在您的人际圈中炫出自己的技能。

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完成“使用 Gemini 和 Imagen 构建实际 AI 应用”技能徽章入门课程，展示您在以下方面的技能：图像识别、自然语言处理、 使用 Google 强大的 Gemini 和 Imagen 模型生成图像、在 Vertex AI 平台上部署应用。

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完成 在 Vertex AI 中设计提示入门技能徽章课程，展示以下方面的技能： Vertex AI 中的提示工程、图片分析和多模态生成式技术。探索如何编写有效的提示，指导生成式 AI 输出， 以及将 Gemini 模型应用于真实的营销场景。

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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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众所周知，机器学习是发展最快的技术领域之一， Google Cloud Platform 在推动其发展方面发挥了重要作用。 GCP 提供了一系列 API，几乎可以满足任何机器学习作业的需求。在 本入门课程中，您将了解机器学习在语言处理方面的运用， 通过实操实验学习 如何从文本中提取实体，执行情感和语法分析，以及 使用 Speech-to-Text API 进行转写。

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大数据、机器学习和人工智能是当今计算领域的热门话题， 但这些领域的专业性很强，因而很难找到 入门资料。幸运的是，Google Cloud 在这些领域提供了方便用户使用的服务， 通过本入门级课程，您可以 开始学习使用 BigQuery、Cloud Speech API 和 Video Intelligence 等工具。

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探索生成式 AI - Vertex AI 课程汇集了多组实验， 指导用户在 Google Cloud 平台上运用生成式 AI。参与实验，您将了解 如何使用 Vertex AI PaLM API 系列模型，包括 text-bison、chat-bison 和 textembedding-gecko。您还将了解提示设计、最佳实践， 以及如何使用生成式 AI 进行构思、文本分类、文本提取、文本 总结等任务。您还将学习如何通过 Vertex AI 自定义训练对基础模型进行调优， 并将模型部署到 Vertex AI 端点。

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