Earlier this year, we launched the Google Cloud skills challenge, which provides 30 days of free access to training to build your cloud knowledge and an opportunity to earn skill badges that showcase your Google Cloud competencies. Today, we’re adding a Native App Development track to the skills challenge, joining the Getting Started, Data Analytics, Kubernetes, Machine Learning (ML) and Artificial Intelligence (AI) tracks.
The Native App Development track is designed for cloud developers who want to learn to build serverless web apps and Google Assistant applications on Google Cloud using Cloud Run and Firebase. Specifically, you’ll have an opportunity to earn three skill badges in the Native App Dev track: Serverless Firebase Development, Serverless Cloud Run Development, and Build Interactive Apps with Google Assistant. To earn a skill badge, you complete a series of hands-on labs and take a final assessment challenge lab to test your skills.
Here’s an overview of each badge.
Serverless Firebase Development
To earn this skill badge, you’ll learn how to build serverless web apps, import data into a serverless database, and build Google Assistant applications using Firebase, Google’s backend-as-service platform for creating mobile and web applications.
Serverless Cloud Run Development
For this badge, you’ll discover how to use Cloud Run, a fully managed serverless platform, to connect and leverage data stored in Cloud Storage. You’ll learn how to use Cloud Run to build a resilient, asynchronous system with Pub/Sub, build a REST API gateway as well as build and expose services.
Build Interactive Apps with Google Assistant
To earn the final skills badge, you’ll build Google Assistant applications by creating a project in the Actions console, integrating Dialogflow, testing your action in the Actions simulator, and adding Cloud Translation API to your assistant application.
Ready to jump into the skills challenge? Sign up here.
By: Taryn Hartzell (Digital Badges Program Manager, Google Cloud)
Source: Google Cloud Blog