June B3 · 15 sessions · prepare in order
Every session mapped to the exact videos that prepare you for it, in the order you should watch them. Tick things off as you go — the page remembers, and always tells you what is next.
Start here
Tick a session once you have watched its videos.
Statistics appears in neither of your Python playlists. It exists in exactly two places, and they are good at different things.
Source one
Seven videos, about 10 hours. Same organisation, same teaching style, same 90–110 minute rhythm as your own classes.
Source two
42 lectures, about 9 hours 43 minutes. Tightly structured, short lectures, covers everything the playlist misses.
| Topic | Playlist | Udemy | Watch |
|---|---|---|---|
| Types of data, scales, sampling | — | §5, 6 lectures | Udemy only |
| Central tendency, dispersion, shape | partial (076) | §6, 8 lectures | Udemy |
| Correlation & covariance | — | §6, 39 min | Udemy only |
| Probability rules, conditional | 074, 075 | §8 (Bayes) | Playlist first |
| Binomial, Poisson, PDF/CDF | — | §7, 5 lectures | Udemy only |
| Normal distribution, z-scores | 072, 073 | §7, 2 lectures | Both |
| Central limit theorem | — | §7, 11 min | Udemy only |
| Confidence intervals | — | §8, 8 min | Udemy only |
| Hypothesis testing, p-values | 070, 071 | §8, 3 lectures | Both |
| t-test, chi-square, ANOVA | glancing | §8, 8 lectures | Udemy |
| A/B testing worked example | 070 | — | Playlist only |
Fifteen steps in teaching order. Each one lists exactly what to watch, how long it takes, and the one thing to prepare before you stand up.
The playlist is reverse-chronological, so the numbers count down.
Statistics lives in sections 5 through 8. Udemy does not allow direct links to individual lectures, so open the course and use the section names.
Udemy §7
Uniform, Log Normal, Power Law and Pareto — about 39 minutes. Real distributions, but not what a fresher analyst is hired on. Skip unless you finish early.
Playlist
Videos 001–069 are machine learning and linear algebra; 077–100 are Python fundamentals your batch already has. None of it is statistics.
Before session 9 you need scipy and statsmodels installed.
Run pip install scipy statsmodels and confirm the import works outside class.