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Introduction to GIS and Spatial Data Science

This repository contains assignments and projects completed for the course Introduction to GIS and Spatial Data Science, offered Winter 2025 from the UCLA Luksin School of Public Affairs.

Course Description

This course exposes students to the foundations of spatial data science. Where once there was a dearth of available digital information, we now live in a world of too much data. How can these data be transformed into human expressions and narratives, and how can these be represented spatially? Our understanding of social phenomena through spatial constructs in urban data allows us to address location-based questions on social justice, the environment, transportation, community development and design, amongst many other themes, and how these factors may affect different population groups in different ways.

This course prepares students for challenges in urban data beyond off-the-shelf cartographic approaches. It looks at the various components of data’s journey—acquisition, exploration, modeling, and communication through visualization—and how it enables and advances your research from a data science perspective.

We begin with an introduction to various data science tools, and review the basics of programming with Python. Once a foundation of Python programming and data wrangling is achieved, spatial analysis through Python Libraries, and subsequently, through advanced geoprocessing will be introduced. All lessons are be based on “real” data with analytical methods addressing relevant and contemporary urban problems.

Personal Introduction

Cameron Manning (cmanning@ucla.edu), Master of Public Policy, 2025

Cameron is a second year MPP student with a focus on quantative analysis methods. He holds bachelors degree in Business Data Analytics, and is familiar with tools including Python, R, Tableau, Looker for data science. He has special interests in public policies related to democracy, K12 education, mental health, and boys and men.

Personal Objectives

Cameron is taking this course to sharpen his Python skills, and learn data analysis techniques specific to spatial analysis. He intends for this course's final project to satisfy the requirements of the UCLA Luskin School of Affairs Certificate in Data Analysis.

Project

The course is organized around the completion of a 10-week project.

Initial Project Ideas

  • Voting Policy in Los Angeles County
  • Mental Healthcare Prevalence in Selected California Counties (degree capstone project)
  • Education Acheievement Gender Gap

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