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시뮬레이션이 아닌 실제 환경에서 클라우드를 직접 경험해 볼 수 있도록 Google Cloud Platform 및 Amazon Web Services의 임시 사용자 인증 정보를 제공해 드립니다. 30분의 간단한 개별 실습부터 수일간 진행되는 과정까지 준비되어 있으며 입문 레벨부터 전문가 레벨까지 레벨별로 진행됩니다. 수업 유형에는 강의형 또는 사용자 주도형이 있으며 머신러닝, 보안, 인프라, 앱 개발 등 다양한 주제로 수업이 진행됩니다.
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 it was designed specifically with Google Cloud Platform integration in mind. In this advanced-level quest, you will get hands-on practice configuring Docker images and containers, deploying fully-fledged Kubernetes Engine applications, and integrating Slackbot and MongoDB databases with Kubernetes. 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.
Exploring Google Ngrams with Amazon EMR
This lab demonstrates how to launch an Amazon Elastic MapReduce (EMR) cluster for Big Data processing and use Hive with SQL-style queries to analyze data. You will create a Hadoop cluster using Amazon EMR which will allow to run interactive Hive queries against data stored in Amazon S3. You will use Hive to normalize the data in a more useful way, and you will run queries to analyze the data.
Amazon Simple Storage Service(S3) 소개
"본 실습에서는 Amazon S3 버킷을 사용하고, 버킷에 저장된 파일이나 객체를 관리하는 방법을 보여줍니다. AWS Management Console에서 버킷을 생성하고, 객체를 보고, 객체를 이동하고, 객체와 버킷을 삭제하는 방법을 연습합니다. 데모를 보려면 아래 링크로 이동하십시오. https://www.youtube.com/watch?v=Yyraql9A_Rc 실습이 설계된 대로 작동하기 위해서는 자동으로 지정된 리전을 변경하면 안 됩니다."
Creating an Amazon Virtual Private Cloud (VPC) with AWS CloudFormation
This lab will demonstrate how to create an Amazon Virtual Private Cloud (VPC) network using AWS CloudFormation. Note: This lab is a more of a walkthrough of a template rather than "learn how to build it". You will walk through the sections of an AWS CloudFormation template and get explanations for each step. You will then launch the AWS CloudFormation template to create a four-subnet Amazon VPC that spans two Availability Zones and a NAT that allows servers in the private subnets to communicate with the Internet in order to download packages and updates.
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.
Google Cloud Storage - Bucket Lock
In this lab, you learn how to use Google Cloud Storage Bucket Lock to manage object retention.
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.
Google Apps Script: Access Google Sheets, Maps & Gmail in 4 Lines of Code
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인프라 및 DevOps
애플리케이션을 클라우드에서 구현, 배포, 이전, 유지관리해 보세요.
웹사이트 및 앱 개발
클라우드에서 애플리케이션을 개발하는 소프트웨어 엔지니어를 위한 실습입니다.
빅데이터 솔루션을 설계, 빌드, 분석, 최적화해 보세요.
확장성 있는 분산형 머신러닝 모델을 작성합니다.
보안, 백업, 복원
규정 준수 상태를 유지하고 정보, 데이터 애플리케이션, 인프라를 보호하세요.