Lecture Notes

These notes are the written companion to the lectures. Every chapter mixes explanation, runnable Python and figures; the code you see is the code that produced the figures.

How to use them

• Read online. Each chapter has a table of contents on the right and a Code menu at the top to show or hide the source of every figure.
• Run them. Each chapter can be opened in Google Colab from the link at the top of the page, or downloaded as a notebook and run locally.
• Practise. Chapters end with exercises, and the self-assessment quiz draws its questions from the same material.

Before you start

The course assumes you can read and write basic Python. The first lecture assigns a self-study crash course covering the language and the data-science stack (NumPy, pandas, matplotlib) — the three notebooks under Lecture 1 in the sidebar. Work through them in the first week; they are not covered in class.

Data

Datasets used by the chapters are served from this site, so the same code runs locally and on Colab. Each chapter defines

DATA = "https://antoninofurnari.github.io/fad-2627/data/"

and loads its files from there.