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.
BigQuery For Data Analysis
Want to learn the core SQL and visualization skills of a Data Analyst? Interested on how to write queries that scale to petabyte-size datasets? Take the BigQuery for Analyst Quest and learn how to query, ingest, optimize, visualize, and even build machine learning models in SQL inside of BigQuery.
Google Cloud Application Programming Interfaces are the mechanism to interact with Google Cloud Services programmatically. This quest will give you hands-on practice with a variety of GCP APIs, which you will learn through working with Google’s APIs Explorer, a tool that allows you to browse APIs and run their methods interactively. By learning how to transfer data between Cloud Storage buckets, deploy Compute Engine instances, configure Dataproc clusters and much more, Exploring APIs will show you how powerful APIs are and why they are used almost exclusively by proficient GCP users. Enroll in this quest today.
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.
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.
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 Amazon Simple Storage Service (S3)
This lab demonstrates how to use an Amazon S3 bucket and manage files, or object, that are stored in the bucket. You will practice how to create a bucket, add an object, view an object, move an object, and delete an object and bucket in the AWS Management Console.
Google Assistant: Build an Application with Dialogflow and Cloud Functions
In this lab, you will build a Google Assistant application with Dialogflow and Cloud Functions for Firebase.
Continuous Delivery with Jenkins in Kubernetes Engine
In this lab you will deploy and completely configure a continuous delivery pipeline using Jenkins running on Kubernetes Engine and go through the dev - deploy process.
Running a MongoDB Database in Kubernetes with StatefulSets
Containers are becoming a popular way to run and scale applications across multiple cloud providers or on both cloud and on-premise hardware. This lab provides a quick introduction to running a MongoDB database on Kubernetes Engine using Docker.
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.