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.

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  1. 1
    Learn about what probability is, the language we use to define it, and how we can quantify uncertainty!
  2. 2
    Learn how to describe different types of random events.
  3. 3
    Learn 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

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How you'll master it

Stress-test your knowledge with quizzes that help commit syntax to memory

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