Sessions

Slides, scripts and exercises, posted before each session.

Session 1. Projects and first steps (Tue 13 Oct)

Goals. After this session you can:

1. open a Python project in VS Code that has its own environment, and run a script;
2. organise a project so that someone else can rerun it;
3. load a dataset in pandas and inspect it: size, first rows, summary statistics.

Before the session: complete the Setup, read the Bryan memo (see Readings) and the AI rules.

Slides: handout, questions without answers (PDF). The version with answers is posted after the session.

Lab: s1-lab.zip. Unzip it inside your course folder; it contains its own data. Open s1_lab.py and click Run Cell above each step. Steps 1–3 from the slides as one script (under a minute; the last line prints Lab done), then fix an AI-written script: lab01_fix_the_bug.py runs without an error but gives a wrong answer, and you find the bug by testing a case whose answer you know.

Session 2. Working with data (Thu 15 Oct, to be confirmed)

Posted before the session.

Session 3. Combining data (Tue 27 Oct)

Posted before the session.

Session 4. Getting data and scaling up (Thu 29 Oct)

Posted before the session.