Statistics and Probability for Data Science: Solve Data-Driven Problems with Python

This course will explore how fundamental mathematical concepts in statistics and probability can be applied to solve data-driven issues, such as complex supply chain problems for companies like Amazon. We will delve into topics like measures of central tendency in descriptive statistics, the Central Limit Theorem, Hypothesis Testing, and A/B Testing. Through hands-on exercises and a real-world case study, you will gain a deeper understanding of how these concepts can be utilized to make data-driven decisions and optimize supply chain operations.

What you’ll learn and how to apply it

• Gain practical experience in applying statistical and probability concepts to real-world business scenarios
• Understand the importance of statistics and probability in data science and analysis
• Utilize Python and the Scipy library to implement various statistical and probability concepts
• Solve business cases using the skills and knowledge acquired in statistics and probability

This course is for you because

• You are a Data Scientist.
• You are a Data Analyst.
• You are a Mathematics Student.

Prerequisites

• Prerequisites for this course include a strong foundation in high school mathematics and basic Python programming skills.