Data Science Fundamentals: Mathematical Foundations for Machine Learning 🧮

This course provides essential mathematical concepts that form the backbone of data science and machine learning. Key topics include:

• Statistics 📊
  Descriptive and inferential statistics, probability distributions, hypothesis testing

  

• Linear Algebra 📐
  Vectors, matrices, eigenvalues, and their applications in data transformations

  

• Probability Theory 📖
  Conditional probability, Bayesian inference, and random variables

  

• Calculus 📐
  Derivatives, integrals, and optimization techniques for machine learning models

  

For deeper exploration, check out our Machine Learning Algorithms course to see how these math concepts apply in practice! 🚀