Probability & Statistics

Move from statistical thinking and exploratory analysis through probability, distributions, sampling-based inference, Bayesian decisions, and advanced regression models.

Statistics and Probability for Data Science

Twenty-five lessons covering statistical thinking, exploratory data analysis, probability rules, Bayes’ theorem and naïve Bayes, random variables, discrete and continuous distributions, the central limit theorem, confidence intervals, and maximum likelihood estimation.

Advanced Statistical Modeling

Logistic and mixed-effects regression for binary outcomes and clustered data.