完成 Introduction to Generative AI、Introduction to Large Language Models 和 Introduction to Responsible AI 三门课程，赢取技能徽章。通过最终测验，即表明您理解了生成式 AI 的基本概念。
技能徽章是由 Google Cloud 颁发的数字徽章，旨在认可您对 Google Cloud 产品与服务的了解程度。公开您的个人资料并将技能徽章添加到您的社交媒体个人资料中，以此来分享您获得的成就。
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这是一节入门级微课程，旨在解释什么是负责任的 AI、它的重要性，以及 Google 如何在自己的产品中实现负责任的 AI。此外，本课程还介绍了 Google 的 7 个 AI 开发原则。
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这是一节入门级微学习课程，探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能，还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。
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本课程向您介绍扩散模型。这类机器学习模型最近在图像生成领域展现出了巨大潜力。扩散模型的灵感来源于物理学，特别是热力学。过去几年内，扩散模型成为热门研究主题并在整个行业开始流行。Google Cloud 上许多先进的图像生成模型和工具都是以扩散模型为基础构建的。本课程向您介绍扩散模型背后的理论，以及如何在 Vertex AI 上训练和部署此类模型。
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这是一节入门级微课程，旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。
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Welcome to the serverless Pet Theory game! Click "Join this Game".
To modify your player name or avatar, go to your My Account page at https://google.qwiklabs.com.
Points are earned by completing the steps in the lab.... and bonus points are earned for speed! Be sure to complete each lab by selecting the END option to get the maximum points.
Please respect the GCP resource quotas that have been allocated. Otherwise, you'll waste your Game time and gain fewer points.
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Welcome to Diwali Speedrun! Here's some more fun for you this Diwali. Learn the ins and outs of the Google assistant with these interesting game labs. Complete the game labs one by one. The faster you complete the lab objectives, the higher your score. You can take each lab up to 5 times. Good luck!
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With Google Assistant part of over a billion consumer devices, this quest teaches you how to build practical Google Assistant applications integrated with Google Cloud services via APIs. Example apps will use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks. You will build 5 different applications that explore useful and fun tools you can extend on your own. No hardware required! These labs use the cloud-based Google Assistant simulator environment for developing and testing, but if you do have your own device, such as a Google Home or a Google Hub, additional instructions are provided on how to deploy your apps to your own hardware.
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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.
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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model. 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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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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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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在此入门级挑战任务中，您可以使用 Google Cloud Platform 的基本工具和服务，开展真枪实弹的操作实训。“GCP 基本功能”是我们为 Google Cloud 学员推荐的第一项挑战任务。云知识储备微乎其微甚至零基础？不用担心！这项挑战任务会为您提供真枪实弹的实操经验，助您快速上手 GCP 项目。无论是要编写 Cloud Shell 命令还是部署您的第一台虚拟机，亦或是通过负载平衡机制或在 Kubernetes Engine 上运行应用，都可以通过“GCP 基本功能”了解该平台的基本功能之精要。点此观看 1 分钟视频，了解每个实验涉及的主要概念。
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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 quest, 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? 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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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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It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of 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 language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.
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Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, Google Cloud provides user-friendly services in these areas, and with this introductory-level quest, so you can take your first steps with tools like Big Query, Cloud Speech API, and AI Platform. Want extra help? 1-minute videos walk you through key concepts for each lab.
Encoder-Decoder Architecture - 简体中文
Earned Nov 19, 2023 EST
Attention Mechanism - 简体中文
Earned Nov 14, 2023 EST
Generative AI Fundamentals - 简体中文
Earned Nov 7, 2023 EST
Introduction to Responsible AI - 简体中文
Earned Nov 7, 2023 EST
Introduction to Large Language Models - 简体中文
Earned Nov 3, 2023 EDT
Introduction to Image Generation - 简体中文
Earned Oct 12, 2023 EDT
Introduction to Generative AI - 简体中文
Earned Sep 19, 2023 EDT
Pet Theory
Earned Nov 20, 2019 EST
Diwali Speedrun
Earned Oct 28, 2019 EDT
![[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant徽章](https://cdn.qwiklabs.com/iN1Y1aBXjPPUZgDdv9GtQCf%2FBp0q3U%2FJg9uWO6RMKoc%3D)
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant
Earned Oct 21, 2019 EDT
Google Developer Essentials
Earned Oct 21, 2019 EDT
BigQuery for Machine Learning
Earned Oct 20, 2019 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned Oct 19, 2019 EDT
Baseline: Deploy & Develop
Earned Oct 13, 2019 EDT
Google Cloud Essentials
Earned Oct 12, 2019 EDT
Machine Learning APIs
Earned Oct 12, 2019 EDT
Intro to ML: Image Processing
Earned Oct 12, 2019 EDT
Intro to ML: Language Processing
Earned Oct 7, 2019 EDT
Baseline: Data, ML, AI
Earned Oct 7, 2019 EDT