Learn the fundamentals of probability and how to quantify and visualize uncertainty.
Time to completeApprox. 5 hours
Certificate of completionIncluded with paid plans
About this course
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.
Syllabus4 lessons • 2 projects • 3 quizzes
Hands-on learningDon’t just watch or read about someone else coding — write your own code live in our online, interactive platform. You’ll even get AI-driven recommendations on what you need to review to help keep you on track.
Projects in this course
Detecting Product Defects with ProbabilityDetermine the number of defective products made at a factory on a given day. Apply concepts from the Poisson distribution, including random variables, the probability mass function, the cumulative distribution function, and expected values.
Sampling Distributions Dance Party!Investigate sampling distributions of Spotify data!
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Practice ProjectsGuided projects that help you solidify the skills and concepts you're learning.
AssessmentsAuto-graded quizzes and immediate feedback help you reinforce your skills as you learn.
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Frequently asked questions about Probability
Probability is a type of math that helps us determine the chances of something happening. For example: When you flip a coin, there’s a 50/50 chance of it landing on either heads or tails. That’s essentially what probability is — calculating the likelihood of a certain outcome or event.