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Data Engineering on Google Cloud Platform

CPB400 - Version:1
This four-day instructor-led class provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The course covers structured, unstructured, and streaming data.
Intended audience
Extracting, Loading, Transforming, cleaning, and validating data Designing pipelines and architectures for data processing Creating and maintaining machine learning and statistical models Querying datasets, visualizing query results and creating reports
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  • Module 1: Google Cloud Dataproc Overview

  • Module 2: Running Dataproc Jobs

  • Module 3: Integrating Dataproc with Google Cloud Platform

  • Module 4: Making Sense of Unstructured Data with Google’s Machine Learning APIs

  • Module 5: Serverless data analysis with BigQuery

  • Module 6: Serverless, autoscaling data pipelines with Dataflow

  • Module 7: Getting started with Machine Learning

  • Module 8: Building ML models with Tensorflow

  • Module 9: Scaling ML models with CloudML

  • Module 10: Feature Engineering

  • Module 11: Architecture of streaming analytics pipelines

  • Module 12: Ingesting Variable Volumes

  • Module 13: Implementing streaming pipelines

  • Module 14: Streaming analytics and dashboards

  • Module 15: High throughput and low-latency with Bigtable

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