Become a cloud expert with hands-on training.
We give you temporary credentials to Google Cloud Platform and Amazon Web Services, so you can learn the cloud using the real thing – no simulations. From 30-minute individual labs to multi-day courses, from introductory level to expert, instructor-led or self-paced, with topics like machine learning, security, infrastructure, app dev, and more, we've got you covered.
NCAA® March Madness®: Bracketology with Google Cloud
In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL and end with building a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
App Modernization with Apigee
Apigee enables you to create APIs and manage them for the benefit of other developers who might need to use your software. Apigee Edge enables you to quickly expose backend services as APIs. These "API Products" offer different capabilities and levels of service, with consumption managed by Apigee. Istio is an open source framework for connecting, securing, and managing microservices, especially services that are hosted in a Kubernetes cluster. This Quest of hands-on labs gives you practice in using Apigee for API creation and management functionality when you decide to modernize an application backend on Google Kubernetes Engine and an Istio based service mesh.
Kubernetes in the Google Cloud
Kubernetes is the most popular container orchestration system and the Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in the Google Cloud. In this advanced-level quest, you will get hands-on practice configuring Docker images and 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.
Challenge: GCP Architecture
This quest of "Challenge Labs" gives the student preparing for the Google Cloud Certified Professional Cloud Architect certification hands-on practice with common business/technology solutions using GCP architectures. Challenge Labs do not provide the "cookbook" steps, but require solutions to be built with minimal guidance, across many GCP technologies. All labs have activity tracking and in order to earn this badge you must score 100% in each lab. This quest is not easy and will put your GCP technology skills to the test. Be aware that while practice with these labs will increase your knowledge and abilities, we recommend additional study, experience, and background in cloud architecture to prepare for this certification.
G Suite: Integrations
This Quest of hands-on labs demonstrates the power of integrating Google Cloud Platform services and tools with G Suite applications. With integration technologies such as App Script and the Clasp Command Line environment, you will create and publish web apps and add-ons for G Suite products: Sheets, Docs, Forms, and Slides. With App Maker you will build a ready-to-use app that has a Google Cloud SQL Database, Google Maps integration, and a Mobile Responsive Design. Other labs create direct connections to GCP data sources-- using the BigQuery API, Sheets, and Slides to collect, analyze and present data.
Networking in the Google Cloud
Networking is a principle theme of cloud computing—it’s the underlying structure of GCP and it’s what connects all your resources and services to one another. This fundamental-level quest will cover essential GCP 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.
This advanced-level quest is unique amongst the other Qwiklabs 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 Dataproc, to Tensorflow, this quest is composed of specific labs that will put your GCP 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.
Introduction to Amazon EC2 Auto Scaling
This lab provides the basic hands-on experience of Amazon EC2 Auto Scaling -- setting up Auto Scaling to automatically launch compute instances in response to conditions that you specify. You will use Auto Scaling via the AWS console to create the basic infrastructure of a Launch Configuration and an Auto Scaling group. You will test the configuration by terminating a running instance and viewing the results as Auto Scaling responds by scaling up and starting another instance.
For the lab to function as written, please DO NOT change the auto assigned region.
[:zh] 使用Amazon EMR分析Ngrams
[:zh] 本实验演示如何运行Amazon Elastic MapReduce（EMR）集群进行大数据分析，并使用Hive以类似SQL查询的方式来分析数据。你将使用Amazon EMR创建一个小的Hadoop集群，对存储在S3上的数据运行交互式的Hive查询。你将使用Hive来把数据规范化处理，创建有意义的数据表并保存在S3上，便于在集群上运行其他作业。
Amazon Simple Storage Service (S3) 简介
本指南旨在向您介绍如何使用 AWS 管理控制台操作 Amazon Simple Storage Service。
使用CloudFormation创建Amazon Virtual Private Cloud(VPC)
本实验展示如何实验CloudFormation来创建亚马逊Virtual Private Cloud（VPC）。注意：本实验更像是一个分步骤展示，而非学习如何创建它。你将查看AWS CloudFormation模版，并了解到模版内每一部分的解释。你将运行该模版来创建一个包含4个子网，跨越2个可用区，包含一个NAT服务器的VPC（NAT服务器允许在私有子网的服务器访问互联网来下载软件包和更新）
Google Assistant: Customizing Templates
In this lab you will learn how to customize an Assistant template by building a flash card application with Cloud Storage and the Cloud Translation API.
Creating an Object Detection Application Using TensorFlow
This lab will show you how to install and run an object detection application. The application uses TensorFlow and other public API libraries to detect multiple objects in an uploaded image.
Image Classification With Cloud ML Engine & Datalab via Cloud Shell
Image classification used to require a lot of training data and huge compute resources. Learn how you can use transfer learning & a pre-trained image model to train with much less data & time using Cloud ML Engine & Datalab.
Video on Demand with AWS Elemental MediaConvert
In this lab, you will utilize the AWS Elemental MediaConvert Service to convert input video into multiple output formats, combine multiple videos into one during the conversion process, add captions/watermarks to the videos, and work with ad insertion metadata.
Build a Serverless Text-to-Speech Application with Amazon Polly
This lab builds a complete serverless application that demonstrates how to convert text-to-speech using Amazon Polly.
Become a Cloud Expert
Infrastructure & DevOps
Implement, deploy, migrate and maintain applications in the cloud.
Websites & App Dev
For software engineers who develop applications in the cloud.
Design, build, analyze, and optimize big data solutions.
Write distributed machine learning models that scale.
Security, Backup & Recovery
Stay compliant and protect information, data applications and infrastructure.