1. Intro to Math for Data Science  

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!