Data Science Fundamentals and Machine Learning
Overview
Subject area
MATH
Catalog Number
342
Course Title
Data Science Fundamentals and Machine Learning
Department(s)
Description
Philosophy of modeling with data. Prediction via linear models and machine learning including support vector machines and random forests. Probability estimation and asymmetric costs. Underfitting vs. overfitting and model validation. Formal instruction of data manipulation, visualization and statistical computing in a modern language. Writing Intensive (W). Recommended corequisites include ECON 382, 387, MATH 341, MATH 343 or their equivalents.
Typically Offered
Spring
Academic Career
Undergraduate
Liberal Arts
Yes
Credits
Minimum Units
4
Maximum Units
4
Academic Progress Units
4
Repeat For Credit
No
Components
Name
Lecture
Hours
6
Requisites
034122