Big Data Developer

It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. The course includes presentations, demonstrations, and hands-on labs.This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP).

Module 1: Introducing Google Cloud Platform

  • Google Platform Fundamentals Overview.
  • Google Cloud Platform Big Data Products.

Module 2: Compute and Storage Fundamentals

  • CPUs on demand (Compute Engine).
  • A global filesystem (Cloud Storage).
  • CloudShell.
  • Lab: Set up a Ingest-Transform-Publish data processing pipeline.

Module 3: Data Analytics on the Cloud

  • Stepping-stones to the cloud.
  • Cloud SQL: your SQL database on the cloud.
  • Lab: Importing data into CloudSQL and running queries.
  • Spark on Dataproc.
  • Lab: Machine Learning Recommendations with Spark on Dataproc.

Module 4: Scaling Data Analysis

  • Fast random access.Datalab.
  • BigQuery.
  • Lab: Build machine learning dataset.

Module 5: Machine Learning

  • Machine Learning with TensorFlow.
  • Lab: Carry out ML with TensorFlow
  • Pre-built models for common needs.
  • Lab: Employ ML APIs.

Module 6: Data Processing Architectures

  • Message-oriented architectures with Pub/Sub.
  • Creating pipelines with Dataflow.
  • Reference architecture for real-time and batch data processing.

Module 7: Summary

  • Why GCP?
  • Where to go from here
  • Additional Resources
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