In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.
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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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Complete the intermediate Manage Data Models in Looker skill badge to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies. 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 course, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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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 Cloud Translation API, and Cloud Natural Language API. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Complete the introductory Build LookML Objects in Looker skill badge 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. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge to demonstrate skills in the following: filtering, sorting, and pivoting data, merging results from different Looker Explores, and using functions and operators to build Looker dashboards and reports for data analysis and visualization. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Earn a skill badge by completing the Get Started with Looker quest, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker. 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, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Earn a skill badge by completing the Develop your Google Cloud Network course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM rols and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches. A skill badge is an exclusivedigital 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, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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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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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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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. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Complete the intermediate Create and Manage Bigtable Instances skill badge to demonstrate skills in the following: creating instances, designing schemas, querying data, and performing administrative tasks in Bigtable including monitoring performance and configuring node autoscaling and replication. 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, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Earn a skill badge by completing the Share Data Using Google Data Cloud course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards. 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 course, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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Complete the introductory Create and Manage Cloud SQL for PostgreSQL Instances skill badge to demonstrate skills in the following: migrating, configuring, and managing Cloud SQL for PostgreSQL instances and databases. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Complete the introductory Create and Manage Cloud Spanner Instances skill badge to demonstrate skills in the following: creating and interacting with Cloud Spanner instances and databases; loading Cloud Spanner databases using various techniques; backing up Cloud Spanner databases; defining schemas and understanding query plans; and deploying a Modern Web App connected to a Cloud Spanner instance. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Earn a skill badge by completing the Migrate MySQL data to Cloud SQL using Database Migration Services quest, where you will learn how to migrate MySQL data to Cloud SQL using Database Migration Services, including how to: connect to Cloud SQL instances using the Cloud Console and with different job types and connectivity options available in Database Migration Service, and migrate MySQL user data when running Database Migration Service jobs. 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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This course is intended to give architects, engineers, and developers the skills required to help enterprise customers architect, plan, execute, and test database migration projects. Through a combination of presentations, demos, and hands-on labs participants move databases to Google Cloud while taking advantage of various services.
This course covers how to move on-premises, enterprise databases like SQL Server to Google Cloud (Compute Engine and Cloud SQL) and Oracle to Google Cloud bare metal.
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Earn the intermediate skill badge by completing the Perform Predictive Data Analysis in BigQuery course, where you will gain practical experience on the fundamentals
of sports data science using BigQuery, including how to create a soccer dataset in BigQuery by importing CSV and JSON files; harness the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on the soccer event data, and evaluate the impressiveness of World Cup goals. 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 course, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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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. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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完成中级技能徽章课程使用 BigQuery 构建数据仓库，展示以下技能： 联接数据以创建新表、排查联接故障、使用并集附加数据、创建日期分区表， 以及在 BigQuery 中使用 JSON、数组和结构体。 技能徽章是 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， 获得数字徽章，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Create ML Models with BigQuery ML，展示您在以下方面的技能： 使用 BigQuery ML 构建和评估机器学习模型，以执行数据预测。 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，即可获得技能徽章， 并在您的社交圈中秀一秀自己的能力。
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完成入门级技能徽章课程“从 BigQuery 数据中挖掘数据洞见”，展示您在以下方面的技能： 编写 SQL 查询、查询公共表、将示例数据加载到 BigQuery 中、 在 BigQuery 中使用查询验证器排查常见的语法错误，以及通过连接到 BigQuery 数据在 Looker Studio 中 创建报告。 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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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Bigtable for analysis. Learners get hands-on experience building streaming data pipeline components on Google Cloud by using QwikLabs.
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Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
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The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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“Google Cloud 基础知识：核心基础架构”介绍在使用 Google Cloud 时会遇到的重要概念和术语。本课程通过视频和实操实验来介绍并比较 Google Cloud 的多种计算和存储服务，并提供重要的资源和政策管理工具。
Serverless Data Processing with Dataflow: Develop Pipelines
Earned Nov 3, 2023 EDT
Responsible AI: Applying AI Principles with Google Cloud - 简体中文
Earned Nov 3, 2023 EDT
Manage Data Models in Looker
Earned Oct 31, 2023 EDT
Use Machine Learning APIs on Google Cloud
Earned Oct 30, 2023 EDT
Build LookML Objects in Looker
Earned Oct 25, 2023 EDT
Prepare Data for Looker Dashboards and Reports
Earned Oct 25, 2023 EDT
Get Started with Looker
Earned Oct 24, 2023 EDT
Develop your Google Cloud Network
Earned Oct 24, 2023 EDT
Generative AI Fundamentals - 简体中文
Earned Oct 23, 2023 EDT
Introduction to Responsible AI - 简体中文
Earned Oct 23, 2023 EDT
Introduction to Large Language Models - 简体中文
Earned Oct 23, 2023 EDT
Introduction to Generative AI - 简体中文
Earned Oct 23, 2023 EDT
Create and Manage AlloyDB Instances
Earned Oct 23, 2023 EDT
Create and Manage Bigtable Instances
Earned Oct 21, 2023 EDT
Share Data Using Google Data Cloud
Earned Oct 21, 2023 EDT
Create and Manage Cloud SQL for PostgreSQL Instances
Earned Oct 21, 2023 EDT
Create and Manage Cloud Spanner Instances
Earned Oct 20, 2023 EDT
Migrate MySQL data to Cloud SQL using Database Migration Service
Earned Oct 19, 2023 EDT
Enterprise Database Migration
Earned Oct 16, 2023 EDT
Perform Predictive Data Analysis in BigQuery
Earned Oct 14, 2023 EDT
Detect Manufacturing Defects using Visual Inspection AI
Earned Oct 14, 2023 EDT
Build a Data Warehouse with BigQuery
Earned Oct 14, 2023 EDT
Create ML Models with BigQuery ML
Earned Oct 14, 2023 EDT
Derive Insights from BigQuery Data
Earned Oct 14, 2023 EDT
Serverless Data Processing with Dataflow: Foundations
Earned Sep 28, 2023 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Sep 27, 2023 EDT
Building Resilient Streaming Analytics Systems on Google Cloud
Earned Sep 26, 2023 EDT
Building Batch Data Pipelines on Google Cloud
Earned Sep 25, 2023 EDT
Modernizing Data Lakes and Data Warehouses with Google Cloud
Earned Sep 22, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Sep 19, 2023 EDT
Google Cloud Fundamentals: Core Infrastructure - 简体中文
Earned Sep 9, 2023 EDT