Data-first, syntax-second

Most "Python for Data" courses teach you syntax with toy CSVs. We do it the other way around: we hand you messy real datasets and walk through the questions a working analyst is actually asked.

You will analyse

• Spotify's public chart data — finding genre trends and predicting break-out artists.
• NYC 311 service requests — mapping noise complaints by neighbourhood and time-of-day.
• NOAA weather sensors — cleaning gappy time-series and producing publication-ready plots.
• A made-up but realistic SaaS funnel dataset — cohort analysis, retention curves, and LTV modelling.

Tools: Python 3.12, Pandas 2.x, NumPy, SQL (DuckDB and Postgres), matplotlib + Plotly, and Jupyter / VS Code notebooks.