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# Math for Data Science Masterclass ## Math for Data Science Masterclass

### Learn about probability, statistics, and more using mathematics that is foundational to the field of data science.

#### What you’ll learn

Math for Data Science Masterclass

• Understand core concepts about data quality and quantity
• Learn about how to measure data with statistics
• Discover how to visualize data with a variety of plot types
• Use combinatorics to calculate permutations and combinations of objects
• Understand the key ideas in using probability to solve problems
• Learn how to use data distributions with real-world data
• Discover the powerful insights from the normal distribution
• Use sampling and the central limit theorem
• Understand hypothesis testing on sample groups
• Cover the basics of linear regression

#### Requirements

• Only basic arithmetic skills are needed, we’ll teach you the rest

#### Description

Welcome to the best online course for learning about the Math behind the field of Data Science!

Working together for the first time, Krista King and Jose Portilla have combined forces to deliver you a best-in-class course experience in how to use mathematics to solve real-world data science problems. This course has been specifically designed to help you understand the mathematical concepts behind the field of data science, so you can have a first-principles level understanding of how to use data effectively in an organization.

Why choose this course?

Combined, Krista and Jose have taught over 3.2 million students about data science and mathematics and their joint expertise means you’ll be able to get the best and clearest mathematical explanations from Krista with framing about real-world data science applications from Jose.  At the end of each section is a set of practice problems developed from real-world company situations, where you can directly apply what you know to test your understanding.

What’s covered in this course?

In this course, we’ll cover:

• Understanding Data Concepts
• Measurements of Dispersion and Central Tendency
• Different ways to visualize data
• Permutations
• Combinatorics
• Bayes’ Theorem
• Random Variables
• Joint Distributions
• Covariance and Correlation
• Probability Mass and Density Functions
• Binomial, Bernoulli, and Poisson Distributions
• Normal Distribution and Z-Scores
• Sampling and Bias
• Central Limit Theorem
• Hypothesis Testing
• Linear Regression
• and much more!

Enroll today and we’ll see you inside the course!

Krista and Jose

#### Who this course is for:

• Anyone interested in learning more about the mathematics behind data science

#### Math for Data Science Masterclass

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