Courses

Network Science of Cities

Course Number:              URSC 689

Course Title:                      Network Science of Cities

Section:                              601

Time:                                  05:30 pm-08:30 pm, Every Tuesday, Fall 2022

Location:                           ARCA 303

Credit Hours:                    3

Instructor:                         Xinyue Ye

Office:                                Langford A 306

E-Mail:                                xinyue.ye@tamu.edu

Course Description

Human being is always curious about how things are related in the world. For thousands of years people are looking for ways to model the world through arts, natural sciences, and social sciences. Network Modeling is one of the prevalence and breakthrough technologies that trying to unravel the mystery of connectivity of the world. Cities are systems composed of flows and networks. Nowadays, urban researchers are using network science with Geographic Information Science (GIS) to explore and analyze the evolving connections among urban elements. In the meantime, more and more virtual networks have spatial characteristics which bring researchers opportunity to study information diffusion and human behavior across urban space. This course will focus on theoretical and substantive themes within network and flow in the cities. Basic knowledge of network elements as well as tools for spatial network analysis and visualization will be covered in this course followed by several case studies.

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Foundations of Research

Course Number:              CARC 601

Course Title:                      Foundations of Research

Section:                              600

Time:                                   02:20 pm-03:35 pm, TR, Fall 2022

Location:                            ARCA 403

Credit Hours:                    3

Instructor:                         Xinyue Ye

Office:                                 Langford A 306

Phone:                                979.458.4306

E-Mail:                               xinyue.ye@tamu.edu

Office Hours:                    TBD, by appointment

Course Description

This course offers an introduction to the research process and its application to problems in planning and design; presentation of philosophy and logic underlying the scientific method; critical analysis of planning and design literature according to each step of the research process: problem definition, hypothesis development, study design, analysis and interpretation of the findings. For doctoral students in the Department of Landscape Architecture & Urban Planning, this course is the first in a series of courses that will introduce you to the research process–how to formulate a research question, justify the need for your research, and develop an approach to your research. While I understand that you may not know what your dissertation will be, this course helps you understand how to develop a dissertation topic and write a draft proposal.

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Programming for Urban and Regional Analytics

Course Number:              URSC 689

Course Title:                     Programming for Urban and Regional Analytics

Section:                             

Time:                                  05:30 pm-08:30 pm, Every Tuesday, Spring 2023

Location:                           ARCA 303

Credit Hours:                    3

Instructor:                         Xinyue Ye

Office:                                ARCA 306

Phone:                               

E-Mail:                               xinyue.ye@tamu.edu

Office Hours:                   TBD, by appointment

Course Description

This course introduces Python programming for Urban and Regional Informatics. Concepts of object-oriented programming and scripting will be presented. Students can develop Python programming/scripting skills fundamental to the automation of urban and regional data manipulation and analysis. Besides receiving hands-on experience through designed labs, students will work on an individual term project. By the end of this course, you will: 1) Understand programming concepts, methods, and approaches; 2) Possess programming technique skills to explore and model urban and regional data.

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