Hi! My name is Miles and I am a first year MURP student concentrating in regional economic development and pursuing a certificate in data analytics. I come from a landscape architecture background and was first introduced to GIS in my undergraduate studies. My interests are many and wide-reaching but I am primarily interested in affordable housing, economic development and environmental planning, and hope to focus my academic and professional career in the space where these sub-fields converge.
The course is intended as both an introduction and in-depth dive into the world of spatial data science through Python, teaching various data collection, visualization, modeling and analysis tools along the way. Geospatial analysis has primarily been conducted through proprietary software but has now been democratized - this course marks the start of this journey of freedom and exploration!
I have a pretty solid grasp on coding in Python from a data science lens but hope to leverage the skills taught in this class to develop a firm understanding of the geospatial tools and packages that are available. My career goals revolve around becoming an urban data scientist (at least in some form) and I am excited of the prospect that this class offers in getting my closer to that goal. I am obsessed with story-telling through visuals and believe this class will help me take my abilities to the next level!
A project idea that I would like to carry over from my previous quarter is assessing the rent burden value by U.S. counties and generating a model that helps describe the variance across the underlying features. In studying California counties, rent burden was not successfully explained solely by the disparity between income and rent prices and I would like to continue this study to determine what variables help explain why some counties suffer from high rent burdens and why others are more resilient. I hope by the end of this class I can better tell the story of rent burden across the U.S. through visually striking maps!
I would also be interested in any projects that involve the following topics:
- Urban pollution, heat island, GHG monitoring
- Labor markets, industry growth
- Rental vs ownership percentages across regions