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
  • Faculty of Science
  • Department of Mathematics
  • Course Structure Diagram with Credits
  • Complex Analysis I
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title MAT321 - Complex Analysis I
Course Type Required Courses
Language of Instruction Türkçe
Laboratory + Practice 2+2
ECTS 5.0
Course Instructor(s) PROFESÖR TANER BÜYÜKKÖROĞLU, PROFESÖR DOKTOR HANDAN AKYAR
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 N/A
Recommended Reading List *Turgut Başkan, Kompleks Fonksiyonlar Teorisi, 6. Baskı, Dora Basım-Yayın Dağıtım, Bursa, 2010. * Zill, D. G. Ve Shanahan, P. D., (Çeviri Editörü: Ahmet Dernek), Kompleks Analiz ve Uygulamaları, 2. Baskıdan Çeviri, Nobel Akademik Yayıncılık, Ankara, 2013. * Ponnusamy, S. ve Silverman, H., Complex Variables with Applications, Birkhauser, Boston, 2006.
Assessment methods and criteria Two midterms and one final written exam
Work Placement N/A
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Complex Numbers
Week - 2 Properties of Complex Numbers
Week - 3 Analytic Geometry with Complex Numbers
Week - 4 Extended Complex Plane and Cordal Distance
Week - 5 Geometric representation of the complex numbers
Week - 6 Complex functions and sequences
Week - 7 Limits and Continuties of Complex Analysis
Week - 8 Derivatives of Complex Functions
Week - 9 Analytic Functions
Week - 10 Harmonic Functions
Week - 11 Elementary Functions
Week - 12 Conjugate function of harmonic function
Week - 13 Geometric Properties of Elementary Functions and Riemann Surfaces
Week - 14 Mobius Transformations

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Drill - Practise
  • Problem Solving
  • Competences
  • Productive
  • Rational
  • Questoning
  • Abstract analysis and synthesis
  • Problem solving
  • Information Management
  • Elementary computing skills
  • Decision making

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 30
2.Midterm Exam 1 30
Final Exam 1 40
Toplam (%) 100
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