Graduate
Institute of Graduate Studies
Urban Design
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Urban Modelling

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
MIMY0419 Urban Modelling 3/0/0 DE TR 6
Course Goals
 In the content of the course, the principles of urban modelling are explained. Logit and probit solid models are studied. Active-based and constraint-based models are examined. Cellular automata system using for terrain simulation and how design decision trees maden are explained. Basic knowledge about Bayesian methods and data mining is given to students in order to analyse and evaluate large databases.    
Prerequisite(s) Course Code Course Name…
Corequisite(s) Course Code Course Name…
Special Requisite(s) The minimum qualifications that are expected from the students who want to attend the course.(Examples: Foreign language level, attendance, known theoretical pre-qualifications, etc.)
Instructor(s) DR. ÖĞR. ÜYESİ ZEYNEP AYŞE GÖKŞİN
Course Assistant(s)
Schedule This course is not offered this semester.
Office Hour(s) Instructor name, day, hours, XXX Campus, office number.
Teaching Methods and Techniques   After teaching basic knowledge, several case studies are conducted. There are two research homeworks during the course. At the end of the course, students are asked to prepare the model of a small size of urban model.
Principle Sources  -
Other Sources  -
Course Schedules
Week Contents Learning Methods
1. Week Introduction to the course verbal expression
2. Week Basic decision making in urban modeling - I verbal expression
3. Week Basic decision making in urban modeling - II Practice
4. Week Methods of urban modeling - I verbal expression
5. Week Methods of urban modeling - II Practice
6. Week I.Research Work Seminar
7. Week Basic urban modeling - I verbal expression
8. Week Basic urban modeling - II Practice
9. Week Advanced urban modeling - I verbal expression
10. Week Advanced urban modeling - II Practice
11. Week II.Research Work Seminar
12. Week Data mining verbal expression
13. Week Bayesian Method - I verbal expression and practice
14. Week Bayesian Method - II Practice
15. Week
16. Week
17. Week
Assessments
Evaluation tools Quantity Weight(%)
Homework / Term Projects / Presentations 2 20
Practice 6 40
Final Exam 1 40


Program Outcomes
PO-1To gain knowledge and understand the socio-economical and spatial components and processes which are both the subjects and the outcomes of an urban design project.
PO-2To gain knowledge and critical awareness about the relations in between urban design and the other disciplines like architecture, urban planning, economy and sociology; and the opportunuties and threats that will arise by these relations.
PO-3Ability to realize an urban design project or a research on urban design in a multidisciplinary process, using both the theoretical and practical knowledge infrastructure, developing new methods and techniques.
PO-4Ability to direct socio-economical and spatial components and processes in the urban design process.
PO-5Ability to make research, to analyse and to criticise in the area of academical knowledge and design processes, using the appropriate techniques, producing original results.
PO-6To gain competency on conducting an indivudial research or project on urban design.
PO-7To gain competency on working as a group member and to work out the complicated processes that will occur during the urban design.
PO-8To gain competency to transfer the knowledge gained using a foreign language, both in verbal and visual way, via contemporary computer programmes and techniques.
PO-9To gain competancy to produce an original academical/scientific research, to present and to discuss in a dialectical framework.
PO-10To gain competency on strategical decision making as a component of the urban design project and to produce original solutions considering ethical values.
Learning Outcomes
LO-1Concept of basic decision processes in urbal modeling
LO-2Basic knowledge about methods of urban modeling
LO-3Basic knowledge about modeling urban models
LO-4Using modeling software as an advanced user
LO-5Basic knowledge about data mining
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10
LO 1
LO 2
LO 3
LO 4
LO 5