- 78% Learning the Open Source GIS Stack: Web Mapping w/ Geoserver

Learning the Open Source GIS Stack: Web Mapping w/ Geoserver

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  • The lowest price of Learning the Open Source GIS Stack: Web Mapping w/ Geoserver was obtained on February 22, 2025 12:05 am.

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Last updated on February 22, 2025 12:05 am
Learning the Open Source GIS Stack: Web Mapping w/ Geoserver
Learning the Open Source GIS Stack: Web Mapping w/ Geoserver

Original price was: $64.99.Current price is: $14.00.

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Learning the Open Source GIS Stack: Web Mapping w/ Geoserver

★★★★★
$64.99
$14.00
 in stock
Udemy.com
as of February 22, 2025 12:05 am

building cloud based GIS solutions for your enterprise

Created by: Arthur Lembo
Professor
Rating:4.36 (59reviews)     283students enrolled

What Will I Learn?

  • You will learn how to install Geoserver,
  • Load spatial and attribute data into Geoserver
  • Server vector, raster, and attribute data on the Internet with Geoserver
  • You will learn how to serve up data from multiple sources like Postgres, Geopackage, SQLite, and shapefiles.
  • You will set up up Geoserver so that it operates like a cloud-based spatial data server.
  • You'll learn how to develop back-end server processing to deliver the results of spatial operations. You'll do this with both SQL and CQL.
  • You will create an application that allows clients and a server to interact with data and Internet users.
  • You will learn the basics of creating a front in web mapping browser, using OpenLayers.
  • You'll learn how to broker the relationship between the Internet user and the back-end server. Once you learn this, you'll be able to adapt just about any client/server application.

Requirements

  • This is advanced stuff, and we'll be serving data on the Internet as well as from Postgres and PostGIS. It is recommended that you are familiar with Postgres.
  • While much of the code will be supplied for you, we'll write some code, so users should be comfortable writing basic scripts.

Target audience

  • GIS users who want to learn how to store their data in the cloud.
  • GIS developers who want to provide their users with cloud-based spatial analysis tools

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