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. |
| Prerequisite |
C or higher in CSE 216 or CSE 219 or CSE 260; AMS 310; CSE major |
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| Textbook | |
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| Course Webpage |