Data Engineering on Google Cloud

IT Technical

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Course Length: 4 Days

Delivered: Virtually


Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data.


To get the most of out of this course, participants should have:


This class is intended for experienced developers who are responsible for managing big data transformations including:



1 - Introduction to Data Engineering

2 - Building a Data Lake

3 - Building a Data Warehouse

4 - Introduction to Building Batch Data Pipelines

5 - Executing Spark on Cloud Dataproc

6 - Serverless Data Processing with Cloud Dataflow

7 - Manage Data Pipelines with Cloud Data Fusion and Cloud Composer

8 - Introduction to Processing Streaming Data

9 - Serverless Messaging with Cloud Pub/Sub

10 - Cloud Dataflow Streaming Features

11 - High-Throughput BigQuery and Bigtable Streaming Features

12 - Advanced BigQuery Functionality and Performance

13 - Introduction to Analytics and AI

14 - Prebuilt ML model APIs for Unstructured Data

15 - Big Data Analytics with Cloud AI Platform Notebooks

16 - Production ML Pipelines with Kubeflow

17 - Custom Model building with SQL in BigQuery ML

18 - Custom Model building with Cloud AutoML

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