Probability Theory



Author: Diana Sadyrova

Course description

We meet probability every day but do not even recognize it! This course will introduce you to the basic terms. You will combine math and programming learning with real-life examples.


Complete all chapters to get certificate


Learn Basic Rules


It's time to dive deeper into the probability theory. Here we will learn basic formulas. The main idea of the section is to help us to understand the term probability using real-life examples.

Random Variable

Bernoulli Trial 1/2

Bernoulli Trial 2/2

Binomial Probability 1/2

Binomial probability

Probabilities of Several Events


Here, we will get acquainted with the rules in probability theory. This section will be more complicated than the previous one. It will be attractive because we are going to work with the real challenges. But it should be noted that we learn some formulas.

Add Probabilities

Calculate Connected Probabilities


Multiply probabilities

Dependent probabilities

Law of Total Probability

Bayes Theorem


Conducting Fascinating Experiments


Doing experiments is always funny, but here we will combine exciting tasks with programming learning. In this section, we will work with the binom object to conduct experiments in Python.

The First Experiment

The Second Experiment

The Third Experiment

Combine Your Knowledge

Discrete Distributions


Distribution is a key to probability learning, but don't be petrified by this term. This section provides you with real-life explanations and relevant formulas.

Discrete Uniform Distribution

Calculate Fascinating Probability

Bernoulli Distribution

Binomial Distribution


Poisson Distribution


Normal Distribution


The normal distribution is the most commonly used one. Here we will work with the distribution with the help of real-life challenges.

Normal Distribution

Challenge 1

–°hallenge 2