CSE357

Course CSE357
Title Statistical Methods for Data Science
Credits 3
Course Coordinator

Andrew Schwartz

Description

This interdisciplinary course introduces the mathematical concepts required to interpret results and subsequently draw conclusions from data in an applied manner. The course presents different techniques for applied statistical inference and data analysis, including their implementation in Python, such as parameter and distribution estimators, hypothesis testing, Bayesian inference, and likelihood.

Bulletin Link

Prerequisite

C or higher in CSE 216 or CSE 260; AMS 310; CSE major

Course Outcomes
Textbook
Major Topics Covered in Course
Laboratory Projects
Course Webpage

CSE357