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.
  • Program in Remote Sensing and Geographical Inform (Distance Learning)
  • Course Structure Diagram with Credits
  • Machine Learning in Geographic Information Systems and Remot
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title UCS588 - Machine Learning in Geographic Information Systems and Remot
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 online.
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended It is recommended that students who will/take this course have some programming knowledge.
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 and 1 final exam.
Work Placement None.
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 Basic Concepts in Machine Learning
Week - 4 Supervised Learning Approach
Week - 5 Classification Problem
Week - 6 Regression Analysis
Week - 7 Unsupervised Learning Approach
Week - 8 Clustering
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 Future Trends and Applications of Artificial Intelligence and Machine Learning in Geographical Information Systems and Remote Sensing

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Drill - Practise
  • Problem Solving
  • Competences
  • Rational
  • Questoning
  • Creative
  • Problem solving
  • Information Management
  • 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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