Module 1: Foundations

2/2 DONE

Sample Space & Events

Defining outcomes, events, and axiomatic definitions.

10 MIN

Python: Random Variables

Simulating discrete and continuous variables using NumPy.

15 MIN

02 Module 2: Bayesian Inference

IN PROGRESS

Priors & Posteriors

Mathematical derivation of Bayes theorem and conjugate priors.

READING

Markov Chain Monte Carlo

Introduction to MCMC sampling methods.

25 MIN

03 Module 3: Hypothesis Testing

Null vs Alternative

Complete Module 2 to unlock