- Intro to urban data analytics, research, and storytelling.
- Intro to common data structures, formats, metrics, variables, and sources for urban data analysis
- Tutorial on spatial data and exploring data in QGIS
- How to make effective charts and maps - lecture and discussion on effective cartography & data visualization
- Tutorial on finding and analyzing census data for demographic / socio-economic analysis and research
- Tutorial on creating a variety of maps and visualizations in QGIS
- Tutorial on querying, downloading, and mapping OpenStreetMap data
- Introduction to Git/GitHub
- Introduction to Python (optional)
- Writing and executing a simple Python script
- Python 101 (data types, conditionals, loops, functions, loading/saving files, etc.)
- Finding and working with libraries
- Jupyter notebook intro (Python + Markdown). Installing packages locally with pip / conda
- Pandas 101 (loading, showing table and subsets, filtering, aggregating, summarizing, descriptive stats, etc.)
- Exploratory data analysis, statistics, and data visualization in Python (with Seaborn)
- Spatial data in Python using GeoPandas (loading data, viewing data, converting non-spatial to spatial data
- Processing spatial data in Python (geocoding, buffers, dissolve, spatial joins, overlays, etc.)
- Relational databases, SQL, postgres
- Spatial databases, PostGIS
- Connecting to databases in Python
- Intro to web-development (HTML, CSS, JS)
- Making a simple web-map (with Maplibre)