[DEPRECATED] Build Interactive Apps with Google Assistant
Earned Jul 19, 2021 EDT
Google Developer Essentials
Earned Jul 18, 2021 EDT
Scientific Data Processing
Earned Jul 18, 2021 EDT
Data Science on Google Cloud
Earned Jul 17, 2021 EDT
Data Science on Google Cloud: Machine Learning
Earned Jul 17, 2021 EDT
基准：数据、机器学习和 AI
Earned Jul 16, 2021 EDT
机器学习简介：语言处理
Earned Jul 16, 2021 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned Jul 15, 2021 EDT
通过 BigQuery ML 创建机器学习模型
Earned Jul 15, 2021 EDT
从 BigQuery 数据中挖掘数据洞见
Earned Jul 15, 2021 EDT
在 Google Cloud 上为机器学习 API 准备数据
Earned Jul 14, 2021 EDT
In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
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随着企业对人工智能和机器学习的应用越来越广泛，以负责任的方式构建这些技术也变得更加重要。但对很多企业而言，真正践行 Responsible AI 并非易事。如果您有意了解如何在组织内践行 Responsible AI，本课程正适合您。
本课程将介绍 Google Cloud 目前如何践行 Responsible AI，以及从中总结的最佳实践和经验教训，便于您以此为框架构建自己的 Responsible AI 方法。
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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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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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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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在本新手级课程中，您将了解 Google Cloud 数据分析工作流，以及可用于探索、分析和直观呈现数据并与相关人员共享发现结果的工具。结合案例研究、实操实验、讲座和测验/演示，本课程展示了如何将原始数据集转化为纯净数据，进而转化为实用的可视化图表和信息中心。无论您是已经在从事数据工作并想了解如何通过 Google Cloud 取得成功，还是在寻求职业发展，都可以借助本课程迈出第一步。几乎所有在工作中执行或使用数据分析的人都可以从本课程中受益。
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Entering the world of cloud computing? You don't have to go alone. Google Cloud partners can help you skip the guesswork and get the most value out of Google Cloud. In today's game, you'll learn how to work with tools and tech from partners like Cisco, Redis, Apache, NetApp, Striim, and Datadog.
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Technology has transformed the retail industry, and the transformation is not stopping. Want to see how to take advantage of the latest tech in your business? (Or job, or future job?) Play now and explore how Google Cloud helps retailers build better - better data, better apps, and better businesses. You'll get hands-on experience with BigQuery ML, Looker, Terraform, and concepts like site reliability. Earn the badge and you'll add one more Arcade point to your collection. Good luck!
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New year, new skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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New year, new skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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New year, New skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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New year, new skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
The goal of DevOps is to combine software development and IT operations into a holistic set of strategies and practices. Want to learn more about how the relationship works? Join a team and challenge yourself to complete each task as quickly and accurately as possible to score points and earn badges.
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These labs help you get started with cloud security basics. At the end of each lab, you'll have hands-on experience with securing your cloud. Complete this game to earn the Level 1 game badge, and you'll be one step closer to completing the challenge. Race the clock to increase your score and watch your name rise on the leaderboard!
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These labs will challenge you to explore advanced cloud security scenarios. It’s OK to take a lab more than once to achieve a great score. Complete this game to earn the Level 3 game badge, and you'll be one step closer to completing the challenge. Race the clock to increase your score and watch your name rise on the leaderboard!
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These labs will give you a deeper understanding of security features in the cloud. These labs are a little more challenging. It’s OK to take a lab more than once to achieve a great score. Complete this game to earn the Level 2 game badge, and you'll be one step closer to completing the challenge. Race the clock to increase your score and watch your name rise on the leaderboard!
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Welcome to the Learn To Earn Cloud Challenge data plus track! "The Google Cloud Certified Professional Data Engineer certification is associated with the highest paying salary in IT," according to the most recent Global Knowledge skills and salary report (published August 2021). Complete this game to earn the Data Plus game badge, and be eligible for a +bonus+ prize in the Learn to Earn Cloud Challenge. See "what's next" below for details and requirements; you’ll need to earn at least 2 additional challenge badges to qualify. You'll learn next-level data skills to add to your resume. Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
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Welcome to the Learn To Earn Cloud Challenge security track! These eight labs give you the keys to understanding GCP's powerful security suite. At the end of each lab, you'll have hands-on experience with securing your cloud. Complete this game to earn the Security game badge, and you'll be one step closer to collecting all four badges (see "what's next" below for more information).
Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
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Welcome to the Learn To Earn Cloud Challenge architecture track! These eight labs give you a blueprint of GCP's building blocks. At the end of each lab, you'll have hands-on experience with another tool or service to add to your resume. Complete this game to earn the Architecture game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
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Welcome to the Learn To Earn Cloud Challenge! These eight labs give you a quick hands-on introduction to eight different GCP tools and services. At the end of each lab, you'll have another skill to add to your list. Complete this game to earn the Essentials game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
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Welcome to the Learn To Earn Cloud Challenge data track! These eight labs give you a deep dive into GCP's data universe. At the end of each lab, you'll have another in-demand skill to add to your list. Complete this game to earn the Data game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
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Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.
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Twelve years ago Lily started the Pet Theory chain of veterinary clinics, and has been expanding rapidly. Now, Pet Theory is experiencing some growing pains: their appointment scheduling system is not able to handle the increased load, customers aren't receiving lab results reliably through email and text, and veteranerians are spending more time with insurance companies than with their patients. Lily wants to build a cloud-based system that scales better than the legacy solution and doesn't require lots of ongoing maintenance. The team has decided to go with serverless technology. For the labs in the Google Cloud Run Serverless Quest, you will read through a fictitious business scenario in each lab and assist the characters in implementing a serverless solution. 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…
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Firebase is a backend-as-service (Bass) platform for creating mobile and web applications. In this quest you will learn to build serverless web apps, import data into a serverless database, and build a Google Assistant application with Firebase and its Google Cloud integrations. 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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For everyone using Google Cloud Platform for the first time, getting familar with gcloud, Google Cloud's command line, will help you get up to speed faster. In this quest, you'll learn how to install and configure Cloud SDK, then use gcloud to perform some basic operations like creating VMs, networks, using BigQuery, and using gsutil to perform operations.
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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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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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Earn a skill badge by completing the Secure Workloads in Google Kubernetes Engine quest, where you learn about security at scale on Google Kubernetes Engine (GKE) including how to: migrate containers from virtual machines to Google Kubernetes Engine, restrict network connections in GKE using firewalls and Network Policies, use role-based access controls (RBAC) in GKE, use Binary Authorization for security controls of your images, secure applications in GKE using 3 access levels: host, network, Kubernetes API, and harden GKE cluster configurations. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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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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本课程提供 Cloud Data Fusion 的实操练习。Cloud Data Fusion 是云原生的 无代码数据集成平台。受益于此，ETL 开发者、数据工程师和分析师 可以利用预构建的转换工具和连接器，轻松构建和 部署流水线，而无需操心编码问题。本课程首先提供了 一个快速入门实验，让学习者熟悉 Cloud Data Fusion 界面。接下来， 学员将尝试运行批处理和实时流水线，并使用内置的 Wrangler 插件对数据执行一些有趣的转换。
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This advanced-level Quest builds on its predecessor Quest, and offers hands-on practice on the more advanced data integration features available in Cloud Data Fusion, while sharing best practices to build more robust, reusable, dynamic pipelines. Learners get to try out the data lineage feature as well to derive interesting insights into their data’s history.
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In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.
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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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Machine Learning is one of the most innovative fields in technology, and the Google Cloud Platform 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 at scale and how to employ the advanced ML infrastructure available on Google Cloud.
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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 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.
完成中级技能徽章课程利用 BigQuery ML 构建预测模型时的数据工程处理， 展示自己在以下方面的技能：利用 Dataprep by Trifacta 构建 BigQuery 数据转换流水线； 利用 Cloud Storage、Dataflow 和 BigQuery 构建提取、转换和加载 (ETL) 工作流； 以及利用 BigQuery ML 构建机器学习模型。
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This advanced-level quest is unique amongst the other catalog 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 Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. 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 the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
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完成在 Cloud Run 上开发无服务器应用技能徽章中级课程， 展示您在以下方面的技能：集成 Cloud Run 与 Cloud Storage 以管理数据， 使用 Cloud Run 和 Pub/Sub 设计弹性异步系统架构， 构建依托 Cloud Run 技术的 REST API 网关，以及在 Cloud Run 上构建和部署服务。
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完成借助 Firebase 开发无服务器应用技能徽章中级课程， 展示您在以下方面的技能：借助 Firebase 设计无服务器 Web 应用架构以及构建无服务器 Web 应用； 利用 Firestore 管理数据库；利用 Cloud Build 自动完成部署流程； 以及将 Google 助理功能集成到您的应用中。
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完成中级技能徽章课程“优化 Google Kubernetes Engine 的费用”， 展示您在以下方面的技能：创建和管理多租户集群、按命名空间监控资源使用情况、 配置集群和 Pod 自动扩缩以提高效率、设置负载均衡以实现最佳资源分布， 以及实现活跃性与就绪性探测以确保应用正常运行并具有成本效益。
完成在 Google Cloud 上使用 Machine Learning API 课程，赢取高级技能徽章。 在本课程中，您将了解以下机器学习和 AI 技术的基本功能： Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。
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Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest and the final assessment challenge lab to receive a skill badge that you can share with your network.
Earn a skill badge by completing the Build Interactive Apps with Google Assistant quest, where you will learn how to build Google Assistant applications, including how to: create an Actions project, integrate Dialogflow with an Actions project, test your application with Actions simulator, build an Assistant application with flash cards template, integrate customer MP3 files with your Assistant application, add Cloud Translation API to your Assistant application, and use APIs and integrate them into your applications. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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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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Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.
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This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.
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This is the second of two Quests of hands-on labs derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this second Quest, covering chapter 9 through the end of the book, you extend the skills practiced in the first Quest, and run full-fledged machine learning jobs with state-of-the-art tools and real-world data sets, all using Google Cloud tools and services.
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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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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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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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完成中级技能徽章课程通过 BigQuery ML 创建机器学习模型，展示您在以下方面的技能： 使用 BigQuery ML 创建和评估机器学习模型，以执行数据预测。
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。
Analyzing and Visualizing Data in Looker
Earned Jul 10, 2024 EDT
Responsible AI: 和 Google Cloud 一起践行 AI 原则
Earned Jun 30, 2024 EDT
在 Vertex AI 中设计提示
Earned Jun 20, 2024 EDT
负责任的 AI 简介
Earned Jun 17, 2024 EDT
大型语言模型简介
Earned Jun 17, 2024 EDT
生成式 AI 简介
Earned Jun 12, 2024 EDT
Google Cloud 数据分析功能简介
Earned May 30, 2024 EDT
Better Together: A Google Cloud Partners Challenge
Earned Feb 15, 2023 EST
Retail Tech
Earned Feb 5, 2023 EST
New Year, New Skills: Blue Challenge (A)
Earned Jan 22, 2023 EST
New Year, New Skills: Red Challenge (A)
Earned Jan 14, 2023 EST
New Year, New Skills: Yellow Challenge (A)
Earned Jan 13, 2023 EST
New Year, New Skills: Green Challenge (A)
Earned Jan 8, 2023 EST
使用 BigQuery 构建数据仓库
Earned Jun 29, 2022 EDT
DevOps: A beautiful relationship
Earned Feb 15, 2022 EST
Learn to Earn Cloud Security Challenge: Level 1
Earned Jan 27, 2022 EST
Learn to Earn Cloud Security Challenge: Level 3
Earned Jan 23, 2022 EST
Learn to Earn Cloud Security Challenge: Level 2
Earned Jan 21, 2022 EST
Learn to Earn Cloud Challenge: Data+
Earned Oct 1, 2021 EDT
Learn to Earn Cloud Challenge: Security
Earned Sep 19, 2021 EDT
Learn to Earn Cloud Challenge: Architecture
Earned Sep 17, 2021 EDT
Learn to Earn Cloud Challenge: Essentials
Earned Sep 16, 2021 EDT
Learn to Earn Cloud Challenge: Data
Earned Sep 15, 2021 EDT
DEPRECATED Applied Data: Blockchain
Earned Sep 13, 2021 EDT
Google Cloud Run Serverless Workshop
Earned Aug 21, 2021 EDT
Build Apps & Websites with Firebase
Earned Aug 21, 2021 EDT
Using the Cloud SDK Command Line
Earned Aug 9, 2021 EDT
DEPRECATED BigQuery for Data Warehousing
Earned Aug 9, 2021 EDT
DEPRECATED BigQuery for Marketing Analysts
Earned Aug 9, 2021 EDT
[DEPRECATED] Secure Workloads in Google Kubernetes Engine
Earned Aug 8, 2021 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned Aug 6, 2021 EDT
在 Cloud Data Fusion 上构建无代码流水线
Earned Aug 5, 2021 EDT
[DEPRECATED] Building Advanced Codeless Pipelines on Cloud Data Fusion
Earned Aug 5, 2021 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned Aug 4, 2021 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned Aug 4, 2021 EDT
Advanced ML: ML Infrastructure
Earned Aug 4, 2021 EDT
Intro to ML: Image Processing
Earned Aug 4, 2021 EDT
Machine Learning APIs
Earned Aug 3, 2021 EDT
面向机器学习的 BigQuery
Earned Aug 3, 2021 EDT
利用 BigQuery ML 构建预测模型时的数据工程处理
Earned Aug 3, 2021 EDT
[DEPRECATED] Data Engineering
Earned Aug 3, 2021 EDT
在 Cloud Run 上开发无服务器应用
Earned Jul 30, 2021 EDT
借助 Firebase 开发无服务器应用
Earned Jul 30, 2021 EDT
优化 Google Kubernetes Engine 的费用
Earned Jul 28, 2021 EDT
为 Compute Engine 实现云负载均衡
Earned Jul 28, 2021 EDT
在 Google Cloud 上使用 Machine Learning API
Earned Jul 28, 2021 EDT
DEPRECATED Explore Machine Learning Models with Explainable AI
Earned Jul 26, 2021 EDT
在 Google Cloud 上部署 Kubernetes 应用
Earned Jul 24, 2021 EDT
在 Google Cloud 上设置应用开发环境
Earned Jul 23, 2021 EDT
开发 Google Cloud 网络
Earned Jul 21, 2021 EDT
[DEPRECATED] Build Interactive Apps with Google Assistant
Earned Jul 19, 2021 EDT
Google Developer Essentials
Earned Jul 18, 2021 EDT
Scientific Data Processing
Earned Jul 18, 2021 EDT
Data Science on Google Cloud
Earned Jul 17, 2021 EDT
Data Science on Google Cloud: Machine Learning
Earned Jul 17, 2021 EDT
基准：数据、机器学习和 AI
Earned Jul 16, 2021 EDT
机器学习简介：语言处理
Earned Jul 16, 2021 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned Jul 15, 2021 EDT
通过 BigQuery ML 创建机器学习模型
Earned Jul 15, 2021 EDT
从 BigQuery 数据中挖掘数据洞见
Earned Jul 15, 2021 EDT
在 Google Cloud 上为机器学习 API 准备数据
Earned Jul 14, 2021 EDT