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Introduction to Serverless: Firebase Development

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. Complete this quest including the the challenge lab at the end to receive an exclusive Google Cloud digital badge. The challenge lab does not provide prescriptive steps, but require solutions to be built with minimal guidance and will put your Google Cloud technology skills to the test!

Insights from Data with BigQuery

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. Complete this quest, including the challenge lab at the end, to receive an exclusive Google Cloud digital badge.

Build and Secure Networks in Google Cloud

Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This fundamental-level quest will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Networking in the Google Cloud will give you the practical experience needed so you can start building robust networks right away. Complete this quest including the the challenge lab at the end to receive an exclusive Google Cloud digital badge. The challenge lab does not provide prescriptive steps, but require solutions to be built with minimal guidance and will put your Google Cloud technology skills to the test!

Introduction to Serverless: Cloud Run Development

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. Complete this quest including the the challenge lab at the end to receive an exclusive Google Cloud digital badge. The challenge lab does not provide prescriptive steps, but require solutions to be built with minimal guidance and will put your Google Cloud technology skills to the test!

Perform Foundational Data, ML, and AI Tasks in Google Cloud

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 Qwiklabs has you covered with this introductory-level quest, so you can take your first steps with tools like Big Query, Cloud Speech API, and AI Platform. Complete this quest, including the challenge lab at the end, to receive an exclusive Google Cloud digital badge. Want extra help? 1-minute videos walk you through key concepts for each lab.

基准：基础架构

如果您是新手云开发人员，希望在GCP Essentials之外寻求动手实践，那么此任务适合您。通过深入研究Cloud Storage和其他关键应用程序服务（如Stackdriver和Cloud Functions）的实验室，您将获得实践经验。通过执行此任务，您将开发适用于任何GCP计划的宝贵技能。 1分钟的视频向您介绍这些实验室的关键概念。

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A Tour of Qwiklabs and Google Cloud

In this first hands-on lab you will access Qwiklabs and the Google Cloud Platform Console and use the basic GCP features: Projects, Resources, IAM Users, Roles, Permissions, APIs, and Cloud Shell.

Creating a Virtual Machine

In this hands-on lab, you’ll learn how to create a Google Compute Engine virtual machine and understand zones, regions, and machine types. To preview, watch the short video Create a Virtual Machine, GCP Essentials.

AI Platform: Qwik Start

In this lab you train and deploy a TensorFlow model to AI Platform for serving (prediction). Watch these short videos Harness the Power of Machine Learning with AI Platform and AI Platform: Qwik Start - Qwiklabs Preview.

Predict Housing Prices with Tensorflow and AI Platform

In this lab you will build an end to end machine learning solution using Tensorflow + AI Platform and leverage the cloud for distributed training and online prediction.

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Introduction to Amazon Aurora

This lab will give you a basic understanding of using Amazon Aurora. You will be shown the basic steps to create an Amazon Aurora instance and then connect to the Amazon Aurora instance. To successfully complete this lab, you should have experience connecting to Microsoft Windows instances using RDP and have a basic knowledge of AWS.

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Using AWS Lambda with Amazon CloudWatch and SNS to Implement a Slack Chat Bot

In this lab you will build a chat bot for Slack, using a Lambda blueprint. Chat bots have the ability to interact with teams and users, respond to commands, and post notifications, giving all conversation participants visibility into team activities. You will build a bot that posts CloudWatch alarms to your Slack channel. Prerequisites: To successfully complete this lab, you should be familiar with AWS Lambda and Amazon CloudWatch through taking the introductory labs. You will need to have or create an account with the online service Slack to complete this lab-- instructions are provided. Familiarity with Slack is helpful, though not required.

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Programming Amazon DynamoDB with .NET

This lab will provide a further understanding of using the AWS Toolkit for .NET and leveraging Amazon DynamoDB for application development. It will demonstrate the basic steps required to install Visual Studio Community Edition and the AWS Toolkit for Visual Studio and to build an application in C# that leverages DynamoDB using the AWS SDK for .NET. To successfully complete this lab, you should be familiar with Visual Studio for C# and have a basic knowledge of launching and connecting to Windows systems in AWS.

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Engineer Data in Google Cloud: Challenge Lab

This challenge lab tests your skills and knowledge from the labs in the Engineer Data in Google Cloud quest. You should be familiar with the content of labs before attempting this lab.

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Using the What-If Tool with Image Recognition Models

In this lab, we demonstrate the use of the what-if-tool for image recognition models.

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