Machine learning and geospatial data in R? In this one-on-one course, you’ll learn how to analyze geospatial data and build machine learning models using the sf, raster, and caret packages. Apply classification, clustering, and regression to real-world datasets and explore applications in GIS, urban planning, and environmental analysis.
Machine learning helps computers recognize patterns and make predictions based on data. When applied to geodata—such as satellite imagery and digital maps—it offers powerful capabilities for spatial analysis.
With R, a widely used programming language for data analysis, you can process large amounts of geodata and build machine learning models. This is used, for example, to detect land-use changes, optimize traffic flows, or calculate flood risks.
A good example is automatic image recognition, which analyzes satellite photos to track urban growth or deforestation. Clustering and classification help group areas based on factors such as population density or infrastructure.
By combining machine learning with geodata, you can develop smarter models that contribute to better decision-making. In this course, you’ll learn how to process geodata, apply algorithms, and visualize results using R and machine learning.
In this course, you’ll learn to apply machine learning to geodata to perform complex spatial analyses. You’ll work with geospatial datasets and learn how to prepare and optimize them for machine learning models.
You’ll get hands-on experience with techniques for recognizing spatial patterns and performing predictive analyses. You’ll use powerful algorithms such as decision trees, random forests, and neural networks to identify trends in geodata.
You’ll also learn to apply clustering and classification to categorize areas based on characteristics such as land use or population density. Additionally, you’ll learn to evaluate and optimize models for reliable and accurate results.
Upon completing this course, you’ll be able to independently apply machine learning techniques in R and analyze geodata for urban planning, environmental research, and GIS projects.
Blended learning combines independent online study with hands-on, interactive sessions, allowing you to gain both theoretical knowledge and practical experience with machine learning for geospatial data analysis. The online modules allow you to set your own pace, while interactive classes teach you how to prepare geodata, train machine learning models, and visualize results. Thanks to direct access to the course materials, you can review and practice the material at any time.
During the hands-on online sessions, you’ll immediately apply the knowledge you’ve gained. You’ll work with real datasets and receive live guidance from experts as you apply clustering, classification, and pattern recognition to geospatial data. By getting hands-on with advanced techniques, you’ll learn to optimize, interpret, and deploy models to generate valuable insights.
The combination of flexible online learning and interactive hands-on experience ensures that you not only understand the basic principles of machine learning in GIS but also learn how to apply this knowledge in realistic scenarios. As a result, upon completing the course, you will be able to independently develop machine learning models and perform geospatial analyses that are directly applicable in your professional field.
You’ll receive 1-on-1 guidance. After signing up, our course coordinator will contact you to schedule your first session.
After completing this course, you will be able to:
Do you have questions about the course content? Or are you unsure whether the course aligns with your learning goals or preferences? Would you prefer an in-house or private course? We’d be happy to help.
After the course, you’ll have another two weeks to ask the instructor questions. Since the instructor is already teaching other courses, it’s best to email your questions to info@geo-ict.nl. Your question will be forwarded to the instructor, and you’ll receive a response within 24 hours.
If you’re a bit further along and encounter practical problems you can’t solve on your own, it’s best to use Online Support. You’ll spend one day online with the instructor and receive personalized one-on-one instruction. All your problems will be resolved, and you’ll have made significant progress.
If you run into problems in practice that you can’t solve on your own, you have two options: you can sign up for a beginner or advanced course, or you can sign up for Online Support.
You’ll spend a day online with an instructor and receive personalized one-on-one instruction. All your problems will be resolved, and you’ll have made significant progress.
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All courses are taught in person. Course hours are from 9:00 AM to 4:00 PM. Coffee, tea, lunch, and a laptop are provided.
Taking a course online is also possible, but we only offer hybrid courses in exceptional cases. If you wish to participate in a course online, please indicate this during registration—select “Online” as the location. If that is not possible, this course will only be offered on-site in Apeldoorn.
Yes, we do this regularly. Our instructor will come to your location and bring laptops for the participants. All you need to do is arrange a classroom at your location.
Please email your requirements to info@geo-ict.nl, and we will send you a quote. Once you’ve confirmed the order, our course coordinator will contact you to schedule the training days.
After each course, participants receive a link to our evaluation portal. There, you can share your feedback on what you liked and didn’t like about the course. We always do our very best, but of course, there may be times when you have a complaint. Click on “Complaints Procedure.” It explains what steps you can take. Geo-ICT Training Center, Netherlands is a member of the Dutch Council for Training and Education (NRTO).
After the course, we will email you a link to our evaluation portal. There, you can log in and fill out an evaluation form, and you can also download your certificate of participation.
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