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Data Engineering, Big Data, and Machine Learning on GCP
Coursera MOOC / Non-credit 0

Data Engineering, Big Data, and Machine Learning on GCP

About this course

This five-week, accelerated online specialization 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. This course teaches the following skills: • Design and build data processing systems on Google Cloud Platform • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow • Derive business insights from extremely large datasets using Google BigQuery • Train, evaluate and predict using machine learning models using Tensorflow and Cloud ML • Enable instant insights from streaming data This class is intended for developers who are responsible for: • 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 >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

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68/100

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16/20

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What you'll learn

  • Design and build data processing systems on Google Cloud Platform
  • Leverage unstructured data using Spark and ML APIs
  • Implement autoscaling data pipelines for batch and streaming data
  • Analyze datasets with Google BigQuery
  • Train and evaluate machine learning models using TensorFlow
$49.00

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