Advanced Spatial Data Science Applications with Python
Blueprint for impact
Get a look at the pillars shaping this course.
While development is still underway, these highlights offer an early look at the skills and outcomes you’ll be working toward:
Explore deep learning in GIS
Learn to work with leading-edge libraries like TensorFlow, PyTorch, and Keras to apply deep learning techniques to geospatial analysis and remote sensing.
Develop and train models
Practice selecting, training, and evaluating deep learning models to solve spatial problems such as object detection, feature extraction, and classification.
Integrate tools with ArcGIS Pro
Understand how commercial tools connect with deep learning libraries, helping you create more powerful and scalable spatial workflows.
Assess model accuracy and performance
Use tools like confusion matrices and F1 scores to evaluate your models, so you can trust and improve the insights they deliver.
"We are designing this course to help learners push the limits of what spatial data science can do with deep learning. With the increasing availability of spatial imagery and sensor data, professionals need skills that go beyond traditional analysis. This course focuses on practical model training and evaluation that connects directly to remote sensing and GIS workflows. I’m especially excited about how it prepares people to solve complex problems in sectors like environmental monitoring, urban planning, and disaster response using advanced machine learning techniques."
Flexible. Applied. Built for business.
Exploring this for your team, not just yourself? You’re in the right place. This course is still in development, making it an ideal time to explore how it could support your workforce goals. Whether you're planning ahead or seeking a strategic fit, we’ll help tailor the experience so it delivers value for your team from day one.
Advanced Spatial Data Science Applications with Python
Take your spatial analytics to the next level with deep learning tools and Python workflows. Learn to train models, extract features, and classify objects in 2D and 3D using cutting-edge spatial data science methods.
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Course description
Course outcomes
The learning experience
Cost
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This course is designed by RIT and delivered on the edX platform. Enrollment is available exclusively at edx.org. Please visit the edX website to explore more detailed information about pricing options, start dates, time commitment and more.
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Ready when you are
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If this course aligns with your goals or your team’s needs, let us know. Your interest helps us plan future sessions and may even accelerate the timeline. We also offer custom options for organizations looking to run tailored versions of this experience.
Hear from the experts
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Insight
"We are designing this course to help learners push the limits of what spatial data science can do with deep learning. With the increasing availability of spatial imagery and sensor data, professionals need skills that go beyond traditional analysis. This course focuses on practical model training and evaluation that connects directly to remote sensing and GIS workflows. I’m especially excited about how it prepares people to solve complex problems in sectors like environmental monitoring, urban planning, and disaster response using advanced machine learning techniques."
Value
Flexible. Applied. Built for business.
Exploring this for your team, not just yourself? You're in the right place. RIT Certified courses and certificates deliver high-impact ROI whether used off the shelf or tailored with our team to align with your workforce strategy. Each offering builds in-demand skills that help teams grow, retain talent, and stay ahead in a world of constant change. We don’t just deliver training. We help you plan for what’s next.
Pathways and certificates
This course is part of a broader mastery certificate.
Explore how it fits into a full learning journey.
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