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.
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Schließen Sie den Skill-Badge-Kurs Sensitive Data Protection in Google Cloud implementieren ab, um Ihre Kenntnisse in den folgenden Bereichen nachzuweisen: Sensitive Data Protection-Dienste verwenden (einschließlich der Cloud Data Loss Prevention API), um sensible Informationen in Google Cloud zu prüfen, zu entfernen und zu de-identifizieren.
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Mit dem Skill-Logo zum Kurs Daten für ML-APIs in Google Cloud vorbereiten weisen Sie Grundkenntnisse in folgenden Bereichen nach: Bereinigen von Daten mit Dataprep von Trifacta, Ausführen von Datenpipelines in Dataflow, Erstellen von Clustern und Ausführen von Apache Spark-Jobs in Managed Service for Apache Spark sowie Aufrufen von ML-APIs, einschließlich der Cloud Natural Language API, Cloud Speech-to-Text API und Video Intelligence API.
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Complete the intermediate Build Global and Regional Load Balancing Solutions skill badge course to demonstrate skills in the following: deploy and utilize an internal client VM within the same VPC network and test traffic distribution, backend infrastructure suitable for a global external application Load Balancer, and backend VM instances and load balancer components using startup scripts and network tags to host a web application service.
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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!
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Mit dem Skill-Logo zum Kurs Cloud Load Balancing in der Compute Engine implementieren weisen Sie Kenntnisse in folgenden Bereichen nach: virtuelle Maschinen in der Compute Engine erstellen und bereitstellen und Netzwerk- und Application Load Balancer konfigurieren.
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Arcade Trail: Data Engineering and Information Protection
Earned Jun 11, 2026 EDT
Sensitive Data Protection in Google Cloud implementieren
Earned Jun 11, 2026 EDT
Daten für ML-APIs in Google Cloud vorbereiten
Earned Jun 11, 2026 EDT
Build Global and Regional Load Balancing Solutions
Earned Jun 10, 2026 EDT
Arcade Base Camp June 2026
Earned Jun 10, 2026 EDT
Cloud Load Balancing in der Compute Engine implementieren
Earned Jun 10, 2026 EDT