Google cloud data engineer certification mastery

What you'll learn
Master core Google Cloud services like Cloud SQL, Spanner, Firestore, Bigtable, and BigQuery.
Learn ETL/ELT workflows, real-time processing with Pub/Sub, Dataflow, and Dataproc.
Understand distributed systems, monitoring, logging, security, and compliance.
Apply ML with model deployment, BigQuery ML, and hands-on projects for real-world readiness.
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Course description
This program is designed for learners who aspire to become experts in cloud-based data engineering. It begins with a comprehensive introduction before diving into the core services of Google Cloud, covering data storage, relational databases such as Cloud SQL and Cloud Spanner, as well as NoSQL solutions like Cloud Firestore and Bigtable. Learners will then explore BigQuery for large-scale data analytics, manage data warehouses, and understand best practices for migrating existing data systems. The curriculum also focuses on practical applications, including data caching with Cloud Memorystore, ETL/ELT workflows, and real-time data processing using Pub/Sub, Dataflow, and Dataproc. Key concepts in distributed systems, monitoring, logging, security, and compliance are introduced to ensure learners can build resilient and scalable pipelines. On the advanced side, the course provides a solid foundation in machine learning—covering model development, deployment, and monitoring—while highlighting the integration of BigQuery ML for AI-powered analytics. The journey concludes with a wrap-up and a hands-on practice exam, equipping participants with the confidence and skills to apply their knowledge in real-world environments.
WHAT'S INCLUDED

