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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Faculty of Computer and Information Sciences
  2. Department of Data Science and Analytics (English)
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  4. Spatial Data Science
  5. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
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Last Updated: 22/07/2026

Code - Course Title Course Type Laboratory + Practice ECTS
VBA403 - Spatial Data Science VII. SEMESTER 3 +0 4.0
Language of Instruction İngilizce
Course Type Required Courses
Course Instructor(s) ARAŞ. GÖR. DR. ÖNDER DORAK
Mode of Delivery Face to face
Place of Delivery
Used Educational Platforms
Prerequisites
Courses Recomended
Recommended Resources
Work Placement
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Geospatial Data Types: Working with vector data
Week - 2 Analyzing raster data formats
Week - 3 Managing coordinate reference systems (CRS)
Week - 4 Spatial Analysis: Executing spatial joins
Week - 5 Performing buffer analysis
Week - 6 Analyzing point patterns
Week - 7 Conducting spatial autocorrelation tests (Moran's I)
Week - 8 Spatial Modeling: Implementing geographically weighted regression
Week - 9 Performing spatial interpolation (Kriging)
Week - 10 Designing interactive web mapping applications
Week - 11 Open Spatial Data: Utilizing satellite imagery
Week - 12 Processing demographic census data
Week - 13 Applying spatial science to urban planning
Week - 14 Environmental monitoring case studies

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%)

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