Learning path
my roadmap to master the three domaines : data science , machine learning and artificial intelligence
By Adam Lachkar
Master key statistical concepts: mean, median, mode, variance, standard deviation, skewness, and kurtosis — the building blocks of understanding how data behaves.
Learn what random variables are and how data distributions work — from PMF and PDF to CDF — the essential foundations before diving into any statistical analysis.
A practical guide to the six core statistical distributions — Normal, Exponential, Uniform, t, Binomial, and Poisson — covering formulas, properties, and real-world use cases.
Understand what outliers are, why they occur, and how to detect them using Z-Score, IQR, Standard Deviation, Isolation Forest, and LOF — with real-world applications.
Learn how to handle outliers effectively — from removal and capping to powerful transformations like Log, Box-Cox, and Yeo-Johnson — and when to keep or drop them.
