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 testingLinear Algebra 📐
Vectors, matrices, eigenvalues, and their applications in data transformationsProbability Theory 📖
Conditional probability, Bayesian inference, and random variablesCalculus 📐
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! 🚀