Machine Learning in GIS and Remote Sensing: 5 Courses in 1 (Udemy.com)
Understand and apply machine learning and deep learning for geospatial analysis (GIS and Remote Sensing) in QGIS, ArcGIS
Created by: Katie Alison
Last updated November 2025
What you will learn
- Fully understand the basics of Machine Learning and Machine Learning in GIS
- Learn the most popular open-source GIS and Remote Sensing software tools (QGIS, SCP, OTB toolbox)
- Learn the market leading GIS software ArcGIS (ArcMap) and ArcGIS Pro
- Learn about supervise and unsupervised learning and their applications in GIS
- Apply Machine Learning image classification in QGIS and ArcGIS
- Run segmentation and object-based image analysis in QGIS and ArcGIS
- Learn and apply regression modelling for GIS tasks
- Understand the main developments in the field of Artificial Intelligence, deep learning and machine learning as applied to GIS
- Complete two independent projects on Machine Learning and Deep Learning
- Understand basics of deep learning as a part of machine learning
- Apply deep learning algorithms , such as convolution neural networks, in GIS with ArcGIS Pro
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.2 out of 5higher than 13% of them
- Reviews539#565 of 1,183 by number of reviews
- Length8.4 hourslonger than 65% of them
- Last updatedNovember 2025more recently than 58% of them
Course Description
Machine Learning and Deep Learning for Geospatial Analysis in QGIS and ArcGIS
This comprehensive course provides a complete introduction to machine learning and deep learning for Geographic Information Systems (GIS) and Remote Sensing. Designed as a 5-in-1 MEGA training, it gives you both the theoretical foundations and practical skills needed to apply advanced algorithms to environmental, land use, and object-based geospatial tasks.
Whether you want to perform land use and land cover (LULC) mapping, run object-based image analysis, or build powerful machine learning models for spatial prediction, this course will guide you step by step using QGIS, ArcGIS, and open-source geospatial tools.
Course Highlights
• In-depth coverage of machine learning and deep learning for GIS and Remote Sensing
• Confidence to apply algorithms such as Random Forest, Support Vector Machines, Decision Trees, and Convolutional Neural Networks
• Hands-on workflows for land use and land cover mapping, object detection, segmentation, and spatial modeling
• Practical experience with QGIS for advanced spatial analysis
• Introduction to Orfeo Toolbox, ArcMap, and ArcGIS Pro
• Completion of two independent GIS projects to showcase your geospatial skills
• Downloadable datasets, exercises, and instructions
Course Focus
This course is designed for learners who already understand basic GIS operations in QGIS or ArcGIS and want to progress to advanced geospatial techniques. You will learn how to integrate machine learning and deep learning with GIS workflows, perform object-based image analysis, and work efficiently with geospatial datasets for real-world applications.
Why Choose This Course
Every lecture is focused on practical application. You will learn how to implement machine learning and deep learning methods directly within GIS environments and how to use these tools to solve real geospatial problems. This course combines theory, hands-on coding, and software-based demonstrations to ensure you gain true applied competency.
What You Will Learn
• Machine learning and deep learning concepts for geospatial analysis
• LULC mapping using supervised learning algorithms
• Regression modeling in ArcGIS
• Object-based image analysis, segmentation, and object detection
• Applying algorithms such as Random Forest, SVM, Decision Trees, and CNNs
• Using Orfeo Toolbox, ArcMap, and ArcGIS Pro for machine learning workflows
• Running complete geospatial projects from data preparation to final maps
• Building two independent GIS projects to demonstrate your skills
Who This Course Is For
This course is ideal for geographers, GIS analysts, Remote Sensing professionals, environmental scientists, programmers, social scientists, geologists, researchers, and anyone who wants to apply machine learning and deep learning to geospatial datasets using QGIS and ArcGIS.
Included in the Course
You will receive access to all datasets, project files, and step-by-step instructions for running machine learning and deep learning algorithms in QGIS and ArcGIS. Future course resources are also included.
Enroll Today
Start mastering advanced geospatial techniques with machine learning and deep learning. Enroll now and begin applying powerful analytical methods to GIS and Remote Sensing tasks using QGIS and ArcGIS.
Instructor Details
- 4.2 Rating
539 Reviews
Katie Alison
Welcome to the World of GIS, Remote Sensing, Machine Learning & Data Science!
Are you ready to develop in-demand skills in GIS, Remote Sensing, Machine Learning, Google Earth Engine, and Data Science?
Whether you are a student, researcher, environmental professional, or aspiring data scientist, you are in the right place. My goal is to help you build practical, real-world skills through structured learning paths, hands-on exercises, and applied projects.
Meet Your Instructor
I am a geospatial scientist, educator, and trainer with extensive international teaching experience in GIS, Remote Sensing, Machine Learning, Environmental Analysis, and Geospatial Data Science. Over the 15+ years, I have had the privilege of teaching thousands of students from around the world and helping them advance their careers, research, and technical skills.
I am passionate about making complex topics accessible, practical, and engaging.
Choose Your Learning Path
Depending on your learning style and goals, you can either follow a detailed step-by-step progression or choose one of the comprehensive all-in-one courses.
Path 1: Step-by-Step Learning Journey
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Reviews
By Hafizullah Rasa on 2/25/2024
This is a good courses that covers a lot of important topics. But the content and software use is quite outdated. I think it is better to update the content and software use as technology improves, and new versions of the software are available.
By Souvik Mahato on 5/26/2022
I will be honest, my concept is yet not clear even after watching it 2x, there is confusion because 5 courses are merged, jumping from one to another, it is difficult to follow and get clear and resource material is not available. I was expecting more from this,
By Valeria on 12/21/2021
An excellent course for GIS and machine learning. The tools have vast opportunities for practical usage. I will be using the concepts gainfully for my work. The instructor has deep knowledge of the subject and her delivery is effective and to the point.
By Anna on 12/21/2021
The course contains valuable information about Machine Learning in GIS and Remote Sensing in QGIS and ArcGIS as well as on cloud computing platforms. I am positive that by applying this concept the quality of my work will significantly increase. The instructor is well-versed in the concept and has a knack for making it simple to understand the concept in her lectures.
By Nadia Delavarpour on 12/13/2021
Hi, It is a good course, and I can tell I learned several new concepts. BUT, it requires a serious revision. There are several confusion in some lectures. Several files, PDF, and imagery data are promised during the lectures but none are provided. In some lectures instructor says she will explain something in the next video but there is not explanation in the next lecture at all. It is not clear how shed download the Kazakhstan data set. I spent several hours to figure it out, but could not. Some of the easy concepts are explained very long but some more important issues are passed so quickly.
By Emin Atabey Peker on 10/24/2021
There are not many courses on such topics and it is very valuable for the lecturer to share her knowledge and experience in this area. I plan to take her other courses as well. But I have some criticisms; Unfortunately, there were too many errors in the QGIS-related sections (there may be version issues), and although the lecturer was quick to turn, no solution was found. The part about deep learning was unfortunately too sloppy, perhaps because the lecturer was giving a separate course on this topic - at least it could have been explained in more detail how the Imagechips folder was created and what it does. In the theoretical part of the course, very few slides were used and the speech was very fast. I think that lecturer read it from a source, not deliberately telling it.
By Кристина on 5/27/2021
During the last two years, I had several courses in Remote Sensing and GIS. I find many of them to be useful and informative but mainly revolve around the very same elementary principles. however, I think this course is a bit unique. The course explains new Gis and remote sensing techniques. I gladly recommend it to all of my friends.
By Марина on 2/3/2021
I am at the beginners' level so for me this course is extremely informative! The instructor is quite knowledgeable, provides clear instructions that are always supported by good examples. I am quite pleased with my choice for the course to introduce myself to Remote Sensing, GIS and Machine Learning!
By Ольга on 12/15/2020
Its a must for everybody. I really enjoyed the whole class and i understand each point.The instructor gave a wonderful class experience. Nice presentation. she makes difficult concepts understand easily.
By Нина Девлетмурзаева on 11/19/2020
This is the best course I have ever taken. Learned a lot from it. The lectures are excellent. Problem sets are challenging. I highly recommend this course for everyone who works with GIS and Remote Sensing!
Quality Score
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Overall Score : 84 / 100









