Scientific Data Processing

6 个小时 Intermediate universal_currency_alt 19 积分

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.

完成此活动，赢取徽章！向世界展示您掌握的技能，拓展云领域的职业之路。

实验

在 BigQuery 和 Cloud SQL 中使用 SQL 簡介

在本研究室中，您將瞭解基本的 SQL 子句，並在 BigQuery 和 Cloud SQL 實際練習執行結構化查詢。

实验

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.

实验

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.

实验

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.

实验

Analyzing Natality Data Using Vertex AI 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.

实验

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.

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挑战任务信息

前提条件

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.

支持的语言

English, français, español (Latinoamérica), 日本語, português (Brasil), and Deutsch

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