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Scientific Data Processing

date_range 6 godz. show_chart Advanced universal_currency_alt Punkty: 30

Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.

Zapisz się na ten kurs, aby śledzić swoje postępy w zdobywaniu odznaki.
Enroll in this on-demand quest
  • Moduł

    Wprowadzenie do SQL w BigQuery i Cloud SQL

    W tym module nauczysz się podstawowych klauzul SQL i wykonasz praktyczne ćwiczenia związane z uruchamianiem zapytań ustrukturyzowanych w BigQuery i Cloud SQL.

  • Moduł

    Rent-a-VM to Process Earthquake Data

    In this lab you spin up a virtual machine, configure its security, access it remotely, and then carry out the steps of an ingest-transform-and-publish data pipeline manually. This lab is part of a series of labs on processing scientific data.

  • Moduł

    Weather Data in BigQuery

    In this lab you analyze historical weather observations using BigQuery and use weather data in conjunction with other datasets. This lab is part of a series of labs on processing scientific data.

  • Moduł

    Distributed Image Processing in Cloud Dataproc

    In this lab, you will learn how to use Apache Spark on Cloud Dataproc to distribute a computationally intensive image processing task onto a cluster of machines.

  • Moduł

    Analyzing Natality Data Using AI Platform and BigQuery

    In this lab you analyze a large (137 million rows) natality dataset using Google BigQuery and Cloud Datalab. This lab is part of a series of labs on processing scientific data.

  • Moduł

    Predict Baby Weight with TensorFlow on AI Platform

    In this lab you train, evaluate, and deploy a machine learning model to predict a baby’s weight. You then send requests to the model to make online predictions. This lab is part of a series of labs on processing scientific data.

  • info
    Quest Info
    Prerequisites
    This Quest requires hands-on experience with GCP data processing and machine learning services like Dataproc, Dataflow, and Cloud ML Engine. It is recommended that the student have at least earned a Badge by completing the hands-on labs in the Baseline: Data, ML, and AI Quest before beginning.