Scientific Data Processing

Advanced 8 Steps 8時間 46クレジット

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.

Infrastructure Data Business Transformation Machine Learning


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.

Quest Outline


SQL for BigQuery と Cloud SQL の概要

このラボでは、基本的な SQL 句について学び、BigQuery と Cloud SQL で実際に構造化クエリを実行します。

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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.


BigQuery の気象データ

このラボでは、BigQuery を使用して気象観測の履歴を分析し、気象データを他のデータセットと組み合わせて使用します。このラボは、科学データを処理するラボシリーズの一部です。

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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.


Distributed Computation of NDVI from Landsat Images Using Cloud Dataflow

In this lab you process Landsat data in a distributed manner using Apache Beam and Cloud Dataflow. This lab is part of a series of labs on processing scientific data.


Datalab と BigQuery による出生率データの分析

このラボでは、Google BigQuery と Cloud Datalab を使用して、1 億 3,700 万行もある大規模な出生率データセットを分析します。このラボは、科学データを処理するラボシリーズの一部です。

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AIプラットホームでの TensorFlow による赤ちゃんの体重予測


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Image Classification of Coastline Images Using TensorFlow on AI Platform

In this lab, you carry out a transfer learning example based on Inception-v3 image recognition neural network. The objective is to classify coastline images captured using drones based on their potential for flood damage.