Track
Google Cloud Data Engineer
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Google Cloud Data Engineer
Prerequisites
There are no prerequisites for this trackCourse
Prepare for the Google Cloud Professional Data Engineer certification with diagnostic questions covering migration, storage, analytics, and automation.
Course
Learn the data engineering role on Google Cloud. Explore data sources, storage solutions, ETL/ELT architectures, BigQuery, Dataform, and Dataproc.
Course
Build modern data lakehouses on Google Cloud using BigQuery, Cloud Storage, Apache Iceberg, BigLake, federated queries, and data governance tools.
Course
Explore streaming data architectures on Google Cloud with Pub/Sub, Managed Kafka, Dataflow, and BigQuery for real-time data processing.
Course
Design and operate batch data pipelines on Google Cloud using Dataflow, Serverless Spark, Cloud Composer, and data validation techniques.
Course
Master Apache Beam and Dataflow foundations including portability, Runner v2, Shuffle Service, Streaming Engine, IAM, quotas, and security.
Course
Develop data pipelines with Apache Beam and Dataflow. Cover transforms, windowing, I/O connectors, schemas, state APIs, Beam SQL, and notebooks.
Course
Operate Dataflow pipelines in production. Learn monitoring, logging, troubleshooting, performance tuning, CI/CD, reliability, and templates.
Course
Use Gemini AI to boost your productivity in BigQuery. Explore data, accelerate code development, and discover visualization workflows.
Course
Work with Gemini AI models in BigQuery for sentiment analysis. Analyze customer reviews using SQL and Python notebooks with Gemini.
Complete
Earn Statement of Accomplishment
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