Syllabus

Week 1: Introduction

• Lecture: Geographic Data Science.
• Tutorial: Tools + Manipulating data in Python - Tidy Data.

Week 2: Modern Computational Environments

• Lecture: Modern Computational Environments.
• Tutorial: Manipulating data in Python - Advanced Tricks.

Week 3: Spatial Data

• Lecture: Spatial Data.
• Tutorial: Manipulating geospatial data in Python.

Week 4: (Geo)Visualization + Choropleths

• Lecture: (Geo)Visualization + Choropleths.
• Tutorial: Mapping deprivation.

Week 5: Spatial Weights

• Lecture: Spatial Weights.
• Tutorial:
  • TEST 1 (1h): Thursday Oct. 24th
  • Spatial Weights with PySAL.

Week 6: ESDA

• Lecture: Exploratory Spatial Data Analysis (ESDA).
• Tutorial: ESDA in Python.

Week 7: Clustering

• Lecture: Clustering.
• Tutorial: Geodemographic analysis.

Week 8: Point Data

• Lecture: Point Data.
• Tutorial: Exploring Twitter patterns.

Week 9

• Lecture: Assignment preparation.
• Tutorial:
  • TEST 2 (1h): Thursday Nov. 21st
  • Assignment Clinic

Week 10: (Spatial) causal inference

• Lecture: Spatial causal inference.
• Tutorial: Assignment Clinic.

Week 11: Geographic Data Science in Action

• Lecture: Geographic Data Science in the wild.
• Tutorial: Assignment Clinic.

ASSIGNMENT due on Thursday, December 5th-2019.