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.
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.
In this introductory-level quest, you will get hands-on practice with the Google Cloud Platform’s fundamental tools and services. GCP Essentials is Qwiklabs’ most popular quest and for good reason—you will come in with little, or no prior cloud knowledge and come out with practical experience that you can apply to any GCP project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine with load balancing, GCP Essentials is a prime introduction to the platform’s features. 1-minute videos walk you through key concepts for each lab.
This fundamental-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 Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your GCP knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
Baseline: Data, ML, AI
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, GCP 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 Cloud ML Engine. Want extra help? 1-minute videos walk you through key concepts for each lab.
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.
Containerized applications have changed the game and are here to stay. With Kubernetes, you can orchestrate containers with ease, and integration with the Google Cloud Platform is seamless. In this advanced-level quest, you will be exposed to a wide range of Kubernetes use cases and will get hands-on practice architecting solutions over the course of 9 labs. From building Slackbots with NodeJS, to deploying game servers on clusters, to running the Cloud Vision API, Kubernetes Solutions will show you first-hand how agile and powerful this container orchestration system is.
If you are a novice cloud developer looking for hands-on practice with GCP’s core infrastructure services, do yourself a favor and enroll in this quest. As a student, you will get practical experience by taking labs that dive into Cloud Storage, computing engines like Kubernetes, and key application services like Stackdriver and Deployment Manager. By taking this quest, you will develop invaluable skills that apply to any GCP project. 1-minute videos walk you through key concepts for each lab.
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.
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.
Introduction to AWS Identity and Access Management (IAM)
This lab shows you how to manage access and permissions to your AWS services using AWS Identity and Access Management (IAM). Practice the steps to add users to groups, manage passwords, log in with IAM-created users, and see the effects of IAM policies on access to specific services.
Setting up Jenkins on Kubernetes Engine
This hands-on lab will show you how to set up Jenkins on Google Kubernetes Engine to help orchestrate your software delivery pipeline.
Loading Data into Google BigQuery for Exploratory Data Analysis
You will learn how to load text data into Google BigQuery and then use that data for rapid exploratory data analysis using Google Cloud Datalab notebooks.
Using the Natural Language API from Google Docs
In this hands-on lab, you will use Apps Script to call the Natural Language API from Google Docs to analyze the sentiment of selected text in the document.
Working with Amazon Redshift
The lab demonstrates how to use Amazon RedShift to create a cluster, load data, run queries and monitor performance. Note: Students will download a free SQL client as part of this lab.
Introduction to Amazon Elastic Block Store (EBS)
This lab takes you through how to create an Amazon Elastic Block Store (EBS) volume, attach it to an Amazon EC2 instance, take a snapshot of the volume, and increase the size and IOPS.
Creating a Persistent Disk
In this hands-on lab, you will learn how to create a persistent disk and use it on a Google Compute Engine virtual machine. You will also learn about zones, regions, and different disk types. Watch the short preview Create a Persistent Disk, GCP Essentials.
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.