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GDE2: Data Engineering on GCP


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GDE2: Data Engineering on GCP


Gain hands-on introduction to designing and building data processing systems that are capable of handling large sets of structured, unstructured, and streaming data on Google Cloud Platform.

Through this course, participants will dive into Google Cloud’s data services by utilizing the power of Big Data to build data processing systems, design end-to-end data pipelines, analyze data and carry out machine learning tasks.


This course is intended for experienced developers who are responsible for managing Big Data transformations. To get the best outcome of this course, participants should have: Completed Google Cloud Fundamentals: Big Data & Machine Learning course OR have equivalent experience.


This program will be conducted with interactive lectures, PowerPoint presentation, discussions, and practical exercise

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Module 1: Introduction to Data Engineering
Module 2: Building a Data Lake & Data Warehouse
Module 3: Introduction to Building Batch Data Pipelines
Module 4: Executing Spark on Cloud Dataproc
Module 5: Serverless Data Processing with Cloud Dataflow
Module 6: Manage Data Pipelines with Cloud Data Fusion and Cloud Composer
Module 7: Introduction to Processing Streaming Data
Module 8: Serverless Messaging with Cloud Pub/Sub
Module 9: Cloud Dataflow Streaming Features
Module 10: High-Throughput BigQuery and Bigtable Streaming Features
Module 11: Advanced BigQuery Functionality and Performance
Module 12: Introduction to Analytics and AI
Module 13: Prebuilt ML model APIs for Unstructured Data
Module 14: Big Data Analytics with Cloud AI Platform Notebooks
Module 15: Production ML Pipelines with Kubeflow
Module 16: Custom Model building with SQL in BigQuery ML & Cloud AutoML
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