Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Graduate School of Sciences
  • Remote Sensing and Geographical Information Syst.
  • Doctorate Degree (Ph.D)
  • Course Structure Diagram with Credits
  • Machine Learning Applications in Geographic Information Syst
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title UCS642 - Machine Learning Applications in Geographic Information Syst
Course Type Elective Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s) DOKTOR ÖĞRETİM ÜYESİ BURCU YILMAZEL
Mode of Delivery The mode of delivery of this course is face to face.
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended There is no other course recommended for this course.
Required or Recommended Resources \\\\\\\"Artificial Intelligence: A Modern Approach\\\\\\\" (3rd edition), Stuart Jonathan Russel and Peter Norvig, 2010
Recommended Reading List -
Assessment methods and criteria There are 1 midterm, 1 final exam, and a term project.
Work Placement Programming assignments about subjects covered in the course
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Introduction to Artificial Intelligence and Machine Learning
Week - 2 Machine Learning in Geographic Information Systems and Remote Sensing
Week - 3 Learning Approaches in Machine Learning
Week - 4 Classification, Regression, Prediction
Week - 5 Clustering, Dimensionality Reduction, Feature Extraction
Week - 6 Decision Trees and Random Forests
Week - 7 Support Vector Machines
Week - 8 Artificial Neural Networks and Deep Learning
Week - 9 Applications of Machine Learning in Geographic Information Systems - Part I
Week - 10 Applications of Machine Learning in Geographic Information Systems - Part II
Week - 11 Applications of Machine Learning in Remote Sensing - Part I
Week - 12 Applications of Machine Learning in Remote Sensing - Part II
Week - 13 Application of Machine Learning Techniques to Problems in Geographic Information Systems and Remote Sensing
Week - 14 Project Presentations

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Drill - Practise
  • Problem Solving
  • Report Preparation and/or Presentation
  • Proje Design/Management
  • Competences
  • Productive
  • Rational
  • Questoning
  • Creative
  • Effective use of Turkish
  • Problem solving
  • Applying theoretical knowledge into practice
  • Information Management
  • Organization and planning
  • Elementary computing skills
  • Decision making
  • To work in interdisciplinary projects
  • Project Design and Management

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%) 0
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