Statistics for Machine Learning

This course in statistics will help you gain a solid understanding of the statistical concepts required to understand the topics in machine learning. While both R and Python contain many packages and libraries with machine learning functionalities, it is important to understand whether the outputs from the packages and libraries align with the data and context you have on hand. This is why having a solid foundation in statistics, probability, linear algebra, and calculus is so important.

• You will be able to define basic terminology in statistics and some common numerical techniques to explore data.
• You will be able to calculate sampling distributions and the central limit theorem, which are the core of inferential statistics.
• You will be able to use statistical inference – estimation and hypothesis testing.
• You will be able to calculate linear regression, the conditions that need to be satisfied and their violations, and cross validation.