Skip to content

Volume 5 — Data Science

From data to defensible conclusions

NumPy, pandas, Polars and PyArrow, then the statistics that stop you fooling yourself: distributions, uncertainty, hypothesis testing and experiment design.

Partly available

Some lessons in this volume are written; the remainder are outlined below and not yet authored.

What you will be able to do

  • Manipulate real datasets fluently in pandas and Polars
  • Quantify uncertainty rather than reporting point estimates
  • Design and analyse an A/B test
  • Recognise Simpson’s paradox, survivorship bias and p-hacking in the wild

Chapters

  1. NumPy: arrays and vectorised thinking
  2. pandas essentials
  3. Polars and the lazy API
  4. PyArrow and the memory format underneath
  5. Exploratory data analysis
  6. Visualisation that communicates
  7. Descriptive statistics
  8. Probability from first principles
  9. Sampling and the central limit theorem
  10. Confidence intervals and hypothesis testing
  11. A/B testing and experiment design
  12. Common statistical traps

Lessons available now

These lessons come from the Version 1 course and are complete.

HTTP, REST APIs & Databases

All volumes