DTSC 5506 - Math and Statistics for Data Science

3 hours

Covers key mathematical and statistical concepts for data science, including linear algebra, calculus, probability theory, random variables, covariance, correlation, causality, statistical distribution, statistical inference, statistical and hypothesis testing, Markov models, sampling methods. Emphasis is placed on applying these mathematical tools to analyze and interpret complex, large data in real-world data science scenarios. Practicing math and statistics programming with Python or other languages.