# Data Science: Probability

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008.

Add a Verified Certificate for $149

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008.

Image

Duration

8 weeks long

Time Commitment

1 - 2 hours per week

Pace

Self-paced

Subject

Collection

Introductory

Credit

Audit for Free

Add a Verified Certificate for $149

Add a Verified Certificate for $149

Platform

edX

Important concepts in probability theory including random variables and independence

How to perform a Monte Carlo simulation

The meaning of expected values and standard errors and how to compute them in R

The importance of the Central Limit Theorem

In this course, part of our Professional Certificate Program in Data Science, you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007–2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability.

We will introduce important concepts such as random variables, independence, Monte Carlo simulations, expected values, standard errors, and the Central Limit Theorem. These statistical concepts are fundamental to conducting statistical tests on data and understanding whether the data you are analyzing is likely occurring due to an experimental method or to chance.

Probability theory is the mathematical foundation of statistical inference which is indispensable for analyzing data affected by chance, and thus essential for data scientists.

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Learn skills and tools that support data science and reproducible research, to ensure you can trust your own research results, reproduce them yourself, and communicate them to others.

Price

Free^{*}

Duration

8 weeks long

Registration Deadline

Available now

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Learn to use R programming to apply linear models to analyze data in life sciences.

Price

Free^{*}

Duration

4 weeks long

Registration Deadline

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A focus on the techniques commonly used to perform statistical inference on high throughput data.

Price

Free^{*}

Duration

4 weeks long

Registration Deadline

Available now