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Lee Cheng Hui

成为会员时间:2019

白银联赛

12100 积分
Build Infrastructure with Terraform on Google Cloud徽章 Build Infrastructure with Terraform on Google Cloud Earned May 29, 2022 EDT
Use Machine Learning APIs on Google Cloud徽章 Use Machine Learning APIs on Google Cloud Earned May 29, 2022 EDT
DEPRECATED Developing Data and Machine Learning Apps with C#徽章 DEPRECATED Developing Data and Machine Learning Apps with C# Earned May 29, 2022 EDT
Create ML Models with BigQuery ML徽章 Create ML Models with BigQuery ML Earned May 29, 2022 EDT
Develop Serverless Applications on Cloud Run徽章 Develop Serverless Applications on Cloud Run Earned May 29, 2022 EDT
Build a Data Warehouse with BigQuery徽章 Build a Data Warehouse with BigQuery Earned May 27, 2022 EDT
BigQuery for Machine Learning徽章 BigQuery for Machine Learning Earned Nov 4, 2021 EDT
Machine Learning APIs徽章 Machine Learning APIs Earned Nov 3, 2021 EDT
NCAA® March Madness®: Bracketology with Google Cloud徽章 NCAA® March Madness®: Bracketology with Google Cloud Earned Nov 3, 2021 EDT
Baseline: Data, ML, AI徽章 Baseline: Data, ML, AI Earned Nov 3, 2021 EDT
Prepare Data for Looker Dashboards and Reports徽章 Prepare Data for Looker Dashboards and Reports Earned Nov 2, 2021 EDT
DEPRECATED BigQuery Basics for Data Analysts徽章 DEPRECATED BigQuery Basics for Data Analysts Earned Nov 2, 2021 EDT
Building Codeless Pipelines on Cloud Data Fusion徽章 Building Codeless Pipelines on Cloud Data Fusion Earned Oct 25, 2020 EDT
Derive Insights from BigQuery Data徽章 Derive Insights from BigQuery Data Earned Oct 25, 2020 EDT
Monitor and Log with Google Cloud Observability徽章 Monitor and Log with Google Cloud Observability Earned Oct 24, 2020 EDT
Data Catalog Fundamentals徽章 Data Catalog Fundamentals Earned Oct 23, 2020 EDT
Data Science on Google Cloud: Machine Learning徽章 Data Science on Google Cloud: Machine Learning Earned Oct 23, 2020 EDT
Google Cloud Solutions II: Data and Machine Learning徽章 Google Cloud Solutions II: Data and Machine Learning Earned Oct 22, 2020 EDT
Intermediate ML: TensorFlow on Google Cloud徽章 Intermediate ML: TensorFlow on Google Cloud Earned Oct 21, 2020 EDT
Prepare Data for ML APIs on Google Cloud徽章 Prepare Data for ML APIs on Google Cloud Earned Oct 21, 2020 EDT
Intro to ML: Language Processing徽章 Intro to ML: Language Processing Earned Oct 20, 2020 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant徽章 [DEPRECATED] OK Google: Build Interactive Apps with Google Assistant Earned Oct 20, 2020 EDT
BigQuery for Data Warehousing徽章 BigQuery for Data Warehousing Earned Oct 19, 2020 EDT
Intro to ML: Image Processing徽章 Intro to ML: Image Processing Earned Oct 18, 2020 EDT
Getting Started with Go on Google Cloud徽章 Getting Started with Go on Google Cloud Earned Oct 17, 2020 EDT
Google Cloud Run Serverless Workshop徽章 Google Cloud Run Serverless Workshop Earned Oct 16, 2020 EDT
Build a Website on Google Cloud徽章 Build a Website on Google Cloud Earned Oct 16, 2020 EDT
Set Up an App Dev Environment on Google Cloud徽章 Set Up an App Dev Environment on Google Cloud Earned Oct 16, 2020 EDT
DEPRECATED Application Development - Python徽章 DEPRECATED Application Development - Python Earned May 3, 2020 EDT
DEPRECATED Application Development - Java徽章 DEPRECATED Application Development - Java Earned May 3, 2020 EDT
Google Kubernetes Engine Best Practices徽章 Google Kubernetes Engine Best Practices Earned May 3, 2020 EDT
Cloud Logging徽章 Cloud Logging Earned May 3, 2020 EDT
[DEPRECATED] Deploying Applications徽章 [DEPRECATED] Deploying Applications Earned May 3, 2020 EDT
Baseline: Deploy & Develop徽章 Baseline: Deploy & Develop Earned May 2, 2020 EDT
Cloud SQL徽章 Cloud SQL Earned May 2, 2020 EDT
Optimize Your Google Cloud Costs徽章 Optimize Your Google Cloud Costs Earned May 1, 2020 EDT
Security & Identity Fundamentals徽章 Security & Identity Fundamentals Earned May 1, 2020 EDT
Baseline: Infrastructure徽章 Baseline: Infrastructure Earned May 1, 2020 EDT
DevOps Essentials徽章 DevOps Essentials Earned May 1, 2020 EDT
VM Migration徽章 VM Migration Earned Apr 30, 2020 EDT
Kubernetes in Google Cloud徽章 Kubernetes in Google Cloud Earned Apr 30, 2020 EDT
Understand Your Google Cloud Costs徽章 Understand Your Google Cloud Costs Earned Apr 29, 2020 EDT
Google Cloud Essentials徽章 Google Cloud Essentials Earned Apr 23, 2020 EDT

Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization. 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 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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C# has powered Windows .NET application development for nearly two decades and Google Cloud is committed to supporting developers getting their .NET workloads up and running on Google Cloud. In this quest, you will learn how to run C# apps in Google Cloud, and specifically how to take your apps to the next level by interfacing them with the big data and machine learning APIs that are accessible now from C#. By enrolling in this quest you will see firsthand how seamlessly Google Cloud integrates with .NET workloads and what the possibilities are for leveraging big data and ML services in your own C# projects.

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「完成 Create ML Models with BigQuery ML 技能徽章中階課程,即可證明您具備下列技能: 使用 BigQuery ML 建立及評估機器學習模型,做出資料預測。 「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 並與他人分享。」

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完成 Develop Serverless Applications on Cloud Run 技能徽章中階課程, 即可證明您具備下列技能:整合 Cloud Run 和 Cloud Storage 以管理資料、 使用 Cloud Run 和 Pub/Sub 架構可復原的非同步系統、 使用 Cloud Run 建構 REST API 閘道,以及在 Cloud Run 建構及部署服務。 「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 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 Build a Data Warehouse with BigQuery 技能徽章中階課程,即可證明您具備下列技能: 彙整資料以建立新資料表、排解彙整作業問題、利用聯集附加資料、建立依日期分區的資料表, 以及在 BigQuery 使用 JSON、陣列和結構體。 「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。完成技能徽章課程及結業評量挑戰研究室, 即可取得技能徽章並與他人分享。

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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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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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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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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.

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完成「Prepare Data for Looker Dashboards and Reports」技能徽章入門課程,即可證明您具備下列技能: 篩選、排序及透視資料、合併不同的 Looker 探索資料,以及使用函式和運算子建構 Looker 資訊主頁和報表,取得資料分析結果和圖表。 「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。 完成這個課程及結業評量挑戰研究室,即可取得技能徽章並與他人分享。

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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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This quest offers hands-on practice with Cloud Data Fusion, a cloud-native, code-free, data integration platform. ETL Developers, Data Engineers and Analysts can greatly benefit from the pre-built transformations and connectors to build and deploy their pipelines without worrying about writing code. This Quest starts with a quickstart lab that familiarises learners with the Cloud Data Fusion UI. Learners then get to try running batch and realtime pipelines as well as using the built-in Wrangler plugin to perform some interesting transformations on data.

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完成 Derive Insights from BigQuery Data 技能徽章入門課程,即可證明您具備下列技能: 撰寫 SQL 查詢、查詢公開資料表、將樣本資料載入 BigQuery、使用 BigQuery 的查詢驗證工具 排解常見語法錯誤,以及在 Looker Studio 中 透過連結 BigQuery 資料建立報表。 「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。完成本技能徽章課程及結業評量挑戰 實驗室,即可取得技能徽章並與他人分享。

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完成 Monitor and Log with Google Cloud Observability 技能徽章入門課程, 即可證明您具備下列技能:監控 Compute Engine 中的虛擬機器、 運用 Cloud Monitoring 監管多項專案、在 Cloud Functions 延伸應用監控和記錄功能、 建立和傳送自訂應用程式指標,以及根據自訂指標設定 Cloud Monitoring 快訊。 「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 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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Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.

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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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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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完成 Prepare Data for ML APIs on Google Cloud 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。 「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。完成本技能徽章課程及結業評量挑戰研究室, 即可取得技能徽章並與他人分享。

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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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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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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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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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Get started with Go (Golang) by reviewing Go code, and then creating and deploying simple Go apps on Google Cloud. Go is an open source programming language that makes it easy to build fast, reliable, and efficient software at scale. Go runs native on Google Cloud, and is fully supported on Google Kubernetes Engine, Compute Engine, App Engine, Cloud Run, and Cloud Functions. Go is a compiled language and is faster and more efficient than interpreted languages. As a result, Go requires no installed runtime like Node, Python, or JDK to execute.

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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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Earn the introductory skill badge by completing the Build a Website on Google Cloud course. This course is based on the series Get Cooking in Cloud, where you learn how to: Deploy a website on Cloud Run; Host a web app on Compute Engine; Create, deploy, and scale your website on Google Kubernetes Engine; Migrate from a monolithic application to a microservices architecture using Cloud Build. 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, 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 Set Up an App Dev Environment on Google Cloud course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub. 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 skill badge that you can share with your network.

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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.

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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Java. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Java applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Java applications straight away.

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Get Anthos Ready. Demand for Google Kubernetes Engine is growing, and customers are looking to Google and its partners to provide in-depth technical knowledge. This first Google Kubernetes Engine-centric Quest of best practices hands-on labs will get you started containerizing to modernize in place , and then managing your deployed apps and services -- with monitoring, tracing, and logging.

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Cloud Logging is a fully managed service that performs at scale. It can ingest application and system log data from thousands of VMs and, even better, analyze all that log data in real time. In this fundamental-level Quest, you learn how to store, search, analyze, monitor, and alert on log data and events from Google Cloud. The labs in the Quest give you hands-on practice using Cloud Logging to maximize your learning experience and provide insight on how you can use Cloud Logging to your own Google Cloud environment.

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The Google Cloud Platform provides many different frameworks and options to fit your application’s needs. In this introductory-level quest, you will get plenty of hands-on practice deploying sample applications on Google App Engine. You will also dive into other web application frameworks like Firebase, Wordpress, and Node.js and see firsthand how they can be integrated with 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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Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.

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This is the second Quest in a two-part series on Google Cloud billing and cost management essentials. This Quest is most suitable for those in a Finance and/or IT related role responsible for optimizing their organization’s cloud infrastructure. Here you'll learn several ways to control and optimize your Google Cloud costs, including setting up budgets and alerts, managing quota limits, and taking advantage of committed use discounts. In the hands-on labs, you’ll practice using various tools to control and optimize your Google Cloud costs or to influence your technology teams to apply the cost optimization best practices.

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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.

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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this course is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions. You will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.

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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this quest you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out! 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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Google Cloud’s four step structured Cloud Migration Path Methodology provides a defined and repeatable path for users to follow when migrating and modernizing Virtual Machines. In this quest, you will get hands-on practice with Google’s current solution set for VM assessment, planning, migration, and modernization. You will start by analyzing your lab environment and building assessment reports with CloudPhysics and StratoZone, then build a landing zone within Google Cloud leveraging Terraform’s infrastructure-as-code templates, next you will manually transform a two-tier application into a cloud-native workload running on Kubernetes, and finally, transform a VM workload into Kubernetes with Migrate for Anthos and migrate a VM between cloud environments.

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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this advanced-level quest, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications. This quest will teach you the practical skills needed for integrating container orchestration into your own workflow. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional Challenge Lab at the end of the Deploy to Kubernetes in Google Cloud Quest to receive an exclusive Google Cloud digital badge.

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This Quest is most suitable for those working in a technology or finance role who are responsible for managing Google Cloud costs. You’ll learn how to set up a billing account, organize resources, and manage billing access permissions. In the hands-on labs, you'll learn how to view your invoice, track your Google Cloud costs with Billing reports, analyze your billing data with BigQuery or Google Sheets, and create custom billing dashboards with Looker Studio. References made to links in the videos can be accessed in this Additional Resources document.

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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.

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