Deep Learning in QGIS

How can you gain deeper insights from geospatial data using deep learning? In this one-on-one course, you’ll discover how to use neural networks in QGIS for object detection, image recognition, and advanced spatial analysis. Through online modules and hands-on assignments, you’ll learn techniques you can apply immediately. By the end of the course, you’ll be able to perform GIS analyses faster and with greater accuracy using deep learning.

Deep Learning in QGIS

Deep Learning is a form of artificial intelligence (AI) that recognizes patterns in large amounts of geospatial data. Combined with QGIS, a powerful open-source GIS platform, this technology enables advanced analyses to be performed on aerial photos, satellite imagery, and other spatial datasets.

By training neural networks, you can use Deep Learning in QGIS for various applications. For example, it helps automatically recognize objects, such as buildings and roads, in aerial photos. Additionally, you can analyze changes in land use, such as urban growth or nature development. Another common application is image classification, which allows satellite images to be categorized quickly and accurately.

By integrating Deep Learning into QGIS, GIS professionals and data analysts can perform geospatial analyses faster and more accurately. This opens up new possibilities for spatial modeling, monitoring, and decision-making.

What will you learn in this Blended Learning course?

In this course, you’ll discover how to use Deep Learning within QGIS to analyze geospatial data more efficiently. You’ll learn how to use AI to perform automated analyses on aerial photos, satellite imagery, and other spatial datasets.

You’ll gain a clear understanding of the fundamentals of Deep Learning and how to apply these techniques in QGIS. Step by step, you’ll learn how to collect and prepare training data, train neural networks, and deploy AI models for spatial analysis.

During the course, you’ll get hands-on experience with image recognition, object detection, and pattern recognition. You’ll discover how to use AI to automatically recognize buildings, roads, or vegetation in aerial photos, for example. You’ll also learn how to analyze changes in land use and optimize geospatial datasets for smart decision-making.

Upon completion, you will be able to apply Deep Learning to your GIS work and perform complex spatial analyses faster and more accurately.

Why choose this Deep Learning in QGIS course?

Blended learning combines independent online study with hands-on, interactive sessions, so you gain both theoretical knowledge and practical experience with Deep Learning in QGIS. The online modules allow you to study at your own pace, while interactive lessons teach you how to apply neural networks, process geospatial data, and integrate AI models into GIS. 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 geodata and receive live guidance from experts as you train and apply AI models to aerial photos and satellite imagery, image recognition, and object detection. By working hands-on with realistic scenarios, you’ll learn to correctly implement Deep Learning in QGIS and optimize your analyses for accurate geospatial insights.

The combination of flexible online learning and interactive hands-on experience ensures that you not only understand the fundamentals of Deep Learning and QGIS, but also know how to apply this knowledge in realistic GIS projects. Upon completion of the course, you will be able to independently develop AI models, automate geospatial analyses, and make data-driven decisions in your field.

Enroll

€395,- (VAT included)
  • Start: 2-hour online session
  • Self-study: Review course materials
  • End: 1-hour online session
Register for this course

You’ll receive 1-on-1 guidance. After signing up, our course coordinator will contact you to schedule your first session.

Leerdoelen

After completing this course, you will be able to:

  • Train and apply AI models yourself in QGIS to automatically analyze aerial photos and satellite imagery.
  • Optimize and prepare geospatial datasets for deep learning applications.
  • Perform object detection and image recognition using neural networks to identify patterns in spatial data.
  • Interpret and optimize deep learning results for accurate and efficient GIS analyses.

Want to know more?

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.

Frequently Asked Questions About Courses

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.

  • Blended learning, also known as hybrid learning, is an educational method that combines traditional face-to-face classes with online learning materials and interactive sessions. This approach offers students flexibility and control over aspects such as the time, place, and pace of learning, while allowing them to benefit from direct interaction with instructors and fellow students. ​
  • At the Geo-ICT Training Center in the Netherlands, blended learning is implemented by having students study largely independently, supplemented by scheduled interactive sessions with an instructor. During these sessions, students can ask questions and discuss complex topics, which fosters a deeper understanding of the course material. All Blended Learning courses begin with a 2-hour online session. The instructor delivers presentations and assigns various exercises and assignments to the student. The student can then work on these independently. After a few weeks, another one-hour online session follows.

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.

 

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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