A COMPLETE 3-Hour Introduction to Spatial and GIS Data in R_1
- Development
- May 12, 2025

A COMPLETE 3-Hour Introduction to Spatial and GIS Data in R, available at $19.99, has an average rating of 4.64, with 31 lectures, based on 7 reviews, and has 24 subscribers.
You will learn about Start a GIS and spatial data project from start to finish, completely in R Become prepared to enter the GIS workforce by elevating your geospatial skillset Learn the most popular libraries and tools for working with spatial data in R No prior coding experience needed, you will learn R from scratch. Create beautiful web maps and static maps for your projects Work with a wide variety of spatial data types, including vector and raster data. Learn how to plot and create beautiful maps Hands-on learning with step-by-step code walkthroughs after each lecture Manipulate and summarize raster data to extract information from satellite imagery and other sources This course is ideal for individuals who are Individuals interested in R, GIS, or spatial data science. It is particularly useful for Individuals interested in R, GIS, or spatial data science.
Enroll now: A COMPLETE 3-Hour Introduction to Spatial and GIS Data in R
Summary
Title: A COMPLETE 3-Hour Introduction to Spatial and GIS Data in R
Price: $19.99
Average Rating: 4.64
Number of Lectures: 31
Number of Published Lectures: 31
Number of Curriculum Items: 31
Number of Published Curriculum Objects: 31
Original Price: CA$139.99
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
If you are entering the field of GIS and want to learn how to get started with R programming and spatial data, this is the course for you. We go over all the basis of how to work with spatial data in an R environment. This course is designed for academics, consultants and individuals looking to enter the GIS field.
Here are a few examples of the projects you will work on:
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Calculate vegetation across Washington and extract values at points of interest
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Interpolate air quality values in areas with missing data
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Calculate the average salary across major neighbourhoods using a Census shape file
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And more!
By the end of this course you will have learnt the following:
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Work with different data types (vector, raster, etc.)
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Conduct GIS analysis
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Create beautiful maps
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Work with real-world data.
More benefits:
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All slides are provided
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All spatial data sets are provided
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Lifetime access to the course, forever.
No prior experience is necessary – just bring your enthusiasm to learn and an eagerness to harness the power of spatial data. By the end of this course, you’ll be equipped with the essential tools to tackle spatial challenges and confidently venture into more advanced data science pathways.
My goal is to help you discover the fascinating intersection of data and location through user-friendly lectures, hands-on exercises, and engaging projects. I will guide you step-by-step, ensuring you feel confident working with Geographic Information Systems (GIS) and exploring diverse spatial datasets.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Chapter 2: Introduction to R programming
Lecture 1: Installing R
Lecture 2: Installing RStudio
Lecture 3: Setting up your RStudio Workspace
Lecture 4: Basic R Code
Lecture 5: Vectors
Chapter 3: Vector Data
Lecture 1: Accessing data for this course
Lecture 2: Install packages and set working directory
Lecture 3: Points: Convert a CSV into a points shape file
Lecture 4: Points: Plotting points data
Lecture 5: Points: Modifying point data frames
Lecture 6: Polygons: Importing a shapefile
Lecture 7: Polygons: Plotting shape files
Lecture 8: Polygons: Exporting data from shape files
Lecture 9: Polygons: Modifying data
Lecture 10: Lines: Importing and modifying data
Lecture 11: Lines: Calculating length of roads in a dataset
Lecture 12: Project: Calculate the road length in each neighbourhood
Chapter 4: Raster Data
Lecture 1: Importing raster data
Lecture 2: Plotting raster data : land surface temperature
Lecture 3: Extracting data from rasters: vegetation data
Lecture 4: Using raster math to calculate new rasters
Lecture 5: Cropping and masking rasters
Lecture 6: Creating a stack of rasters with air pollution data
Lecture 7: Creating your own raster
Chapter 5: Making Maps
Lecture 1: Plotting earthquake data in leaflet
Lecture 2: Plotting csv data in leaflet
Lecture 3: Plotting polygons in leaflet
Lecture 4: Plotting raster data in leaflet
Lecture 5: Interactive maps in tmap
Chapter 6: Conclusion
Lecture 1: Thanks for watching!
Instructors

Priya Patel
Data scientist and Engineer
Rating Distribution
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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