Introduction to Maps in Folium and Python

Welcome to the Introduction to Maps in Folium and Python Course. In this course we will be exploring the different capabilities of the folium library. Folium is a python mapping library that allows you to create maps rapidly with very little and easy to understand code. We will use this library to create a variety of maps for multiple use cases. We will be exploring the most useful objects that the folium library has to offer ranging from Markers, Points, Measure Controls, Tiles, Web Map Tile Services, Layers and much more.

We will also do a bit of preprocessing with the pandas library, in order to prepare our data for meeting the requirements of the maps that we will be building. By using the full capabilities of the tools we will be using, one can build very advanced map applications with very few lines of code.

This course is useful to all levels of experience from beginner to advanced professionals and is very easy to get started with. There are no complex installations and configurations required, as we will use a single platform that includes everything we need such as jupyter notebook.

It is only required that you have python 3 installed and anaconda, as well as an internet connection, in order to download our datasets and libraries. Any operating system is applicable as long as you are able to run jupyter notebooks and use the python 3 compiler. This course is done on a windows 10 machine. After you build your maps you will learn how to share them with anyone.

Basic knowledge

• Very basic understanding of Python
• Little or no understanding of GIS
• Very basic understanding of Programming
• Basic understanding of Data

• GIS Developers at any level
• Python Developers at any level
• Developers at any level
• An interest in data story telling through Maps
• The curious mind

Course Completion Certificate

What will you learn

• Web Mapping with Folium
• Web Mapping
• Python Programming
• Web GIS Programming
• Web Map Tile Services (WMTS)
• Data manipulation and preprocessing

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