Data Science: Probability

About

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.

What you will learn

• 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

Skills you learn

• Securities (Finance)
• Probability Theories
• Financial Crisis
• Monte Carlo Methods
• Statistical Hypothesis Testing
• Probability
• Random Variables
• Statistical Inference
• Data Analysis
• Data Science

Auto Summary

"Data Science: Probability" is an essential course for aspiring data scientists, focusing on the fundamental principles of probability theory. Presented by edX, this foundational course delves into real-world applications through an intriguing case study on the financial crisis of 2007-2008. Over 12 weeks, learners will gain critical insights and skills crucial for data science proficiency. The course is available through both Professional and Starter subscription plans, making it accessible for those at the beginning of their data science journey or looking to strengthen their foundational knowledge in IT and Computer Science. Ideal for anyone aiming to build a robust understanding of probability in data science, this course provides a comprehensive and practical learning experience.