Data Engineering on Google Cloud Platform

The Data Engineering on the Google Cloud Platform course will prepare one to create data loading  & transformation pipelines and apply machine learning algorithms with TensorFlow to the processed data. It will also enable candidates to assess the most appropriate user-facing tool for end-users.
 

Course Outline

 

Making Sense of Unstructured Data with Google’s Machine Learning APIs
  • 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
Serverless Data Analysis with Google BigQuery and Cloud Dataflow
  • Module 5: Serverless data analysis with BigQuery
  • Module 6: Serverless, autoscaling data pipelines with Dataflow
Serverless Machine Learning with TensorFlow on Google Cloud Platform
  • 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
Building Resilient Streaming Systems on Google Cloud Platform
  • 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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