Become a Google Cloud Platform expert with hands-on training.
We give you temporary credentials to Google Cloud Platform, 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.
Esta Quest es la más popular de todas las que ofrecemos y brinda una experiencia directa de Google Cloud. Familiarícese con tareas básicas como poner una VM en marcha, configurar las herramientas clave de la infraestructura o incluso trabajar con conceptos más avanzados de Stackdriver y Kubernetes.
Security & Identity Fundamentals
Security is an uncompromising feature of Google Cloud Platform services, and GCP has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with GCP’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.
Data Science on the Google Cloud Platform
This Quest of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform by Valliappa Lakshmanan, published by O'Reilly Media, Inc. Students are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud Platform tools and services.
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.
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.