Probability
In this unit, we will cover fundamental rules of probability including how to describe random events. We will cover topics such as set theory, conditional probability, joint probability, Bayes rule, probability distributions, and sampling distributions. These concepts are important in order to understand the likelihood of events, fit machine learning models, and perform hypothesis tests.
Codecademy courses have been taken by employees at
- 1Learn about what probability is, the language we use to define it, and how we can quantify uncertainty!
- 2Learn how to describe different types of random events.
- 3Learn how to quantify the statistics of a randomly sampled experiment and visualize the distribution.
What you'll create
Portfolio projects that showcase your new skills
Product Defects
You will be analyzing the number of defective products made at a factory on a given day. You will be applying various concepts from the Poisson distribution, including random variables, the probability mass function, the cumulative distribution function, and expected values.
Sampling Distributions Dance Party!
Let's investigate some sampling distributions of Spotify data!
How you'll master it
Stress-test your knowledge with quizzes that help commit syntax to memory
— Madelyn, Pinterest“I know from first-hand experience that you can go in knowing zero, nothing, and just get a grasp on everything as you go and start building right away.”