Welcome to the Introduction to Maps in R Shiny and Leaflet course. In this course we will be creating a fully functional web gis application using the R programming language. This application will be comprised of different types of maps ranging from point maps to heatmaps, to choropleth maps.
We will also be using different datasets ranging from dataframes to spatial data frames, which we will use to transform and visualize our data on different types of maps, depending on the use case. Once we have completed the course we will be equipped with extremely valuable skills, that we can use to build sophisticated web map applications of any kind and tell spatial data stories that almost anyone can interpret and understand.

Some of the skills you will acquire from taking this course range from:

● Working with spatial data in the R programming language
● Installing and using R studio
● Using the leaflet web mapping library
● Creating a variety of maps and integrating it into a single application
● Building a dashboard in R Shiny
● Creating map legends and colour palettes
● Styling maps using embedded html functions
● Working with dataframes
● Using R terminal operations

WHAT YOU WILL LEARN

● R Programming
● Web Mapping
● Web GIS Programming
● Working with dataframes
● Web mapping with the Leaflet library
● Building a GIS application


WHO THIS COURSE IS FOR

● R programmers at any level
● GIS Developers at any level
● Developers at any level
● An interest in spatial data story telling through Maps
● Anyone who wants to learn GIS programming using R
● The curious mind

1. Introduction
2. Installations and Setup
3. Creating the Earthquake OSM Map
4. Creating the Earthquake Dark Map
5. Creating the Heatmap
6. Creating the Choropleth Map
7. Project Source Code

Edwin Bomela is a Big Data Engineer and Consultant, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. He is currently a consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.