What you will learn
- How to think about uncertainty and randomness
- How to make good predictions
- The story approach to understanding random variables
- Common probability distributions used in statistics and data science
- Methods for finding the expected value of a random quantity
- How to use conditional probability to approach complicated problems
With examples ranging from medical testing to sports prediction, you will gain a strong foundation for the study of statistical inference, stochastic processes, randomized algorithms, and other subjects where probability is needed.
Before you start
Not all units require Calculus, the underlying concepts can be learned concurrently with a Calculus course or on your own for self-directed learners.
Units 1-3 require no calculus or matrices; Units 4-6 require some calculus, no matrices; Unit 7 requires matrices, no calculus.
Previous probability or statistics background not required.
- Instructor-Led: course contains assignments and exams that have specific due dates, and you complete the course within a defined time period.
- Course ends: Dec 6, 2018
Meet Your Instructors
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