Member since 2026
Implementing Cloud Load Balancing for Compute Engine
Earned يونيو 30, 2026 EDT
Arcade Trail: Data Engineering and Information Protection
Earned يونيو 20, 2026 EDT
Prepare Data for ML APIs on Google Cloud
Earned يونيو 20, 2026 EDT
Implement Cloud Collaboration and Productivity Workflows
Earned يونيو 18, 2026 EDT
Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
Raw data is only useful if it is clean, structured, and secure. In this track, you’ll start by processing and preparing data using Dataprep, Dataflow templates, and Apache Spark. You'll learn how to clean up datasets so they are ready for machine learning models. From there, you'll focus on security by working with tools that find and mask sensitive information like personal IDs and credentials. You'll practice redacting critical details and creating safe, de-identified copies of your data in Cloud Storage. By finishing the hands-on challenge labs, you’ll show you can handle big data workflows while keeping confidential information completely safe.
Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Managed Service for Apache Spark, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
Earn an introductory skill badge by completing the Implement Cloud Collaboration and Productivity Workflows course, where you will get introduced to Google's collaborative platform and learn to use Gmail, Calendar, Meet, Drive, Sheets, and AppSheet.