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Getting Started with Spatial Analysis in GeoDa

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By the end of this project, learners will know how to start out with GeoDa to use it for spatial analyses. This includes how to access and download the software, import multiple layers, and a basic overview of GeoDa. Spatial analysis, as a type of data analysis, has been getting increasingly important. The beginnings are often dated back to John Snow’s cholera outbreak maps from the mid-1800s. In 2003, Dr. Luc Anselin at the University of Chicago developed GeoDa, together with his team, to provide free software that digitizes old school pin maps. Today, it is used in various fields to plan cities and infrastructure, create crime maps, emergency management, and visualize finds at archaeological sites. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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Dive into the world of spatial analysis with "Getting Started with Spatial Analysis in GeoDa," a beginner-friendly course perfect for aspiring data scientists and AI enthusiasts. Led by Coursera, this engaging program will equip you with the skills to utilize GeoDa, a powerful tool for spatial data analysis developed by Dr. Luc Anselin. Through this course, you will learn how to access and download GeoDa, import multiple layers, and gain a fundamental understanding of its functionalities. Spanning 120 minutes, this concise yet comprehensive course will guide you through the historical significance of spatial analysis, tracing its origins back to John Snow's pioneering cholera outbreak maps in the 1800s. Today, GeoDa is instrumental in diverse fields such as urban planning, crime mapping, emergency management, and archaeology. This course is available for free and is tailored for learners in the North America region, with efforts underway to extend the experience globally. Whether you are a novice in data science or looking to expand your analytical toolkit, this course offers an excellent foundation to start your journey in spatial analysis.