Course Websites

CS 307 - Model & Learning in Data Sci

Last offered Fall 2024

Official Description

Introduction to the use of classical approaches in data modeling and machine learning in the context of solving data-centric problems. A broad coverage of fundamental models is presented, including linear models, unsupervised learning, supervised learning, and deep learning. A significant emphasis is placed on the application of the models in Python and the interpretability of the results. Course Information: Prerequisite: STAT 207; one of MATH 225, MATH 227, MATH 257, MATH 415, MATH 416, ASRM 406.

Related Faculty

Course Director

Model & Learning in Data SciMLD77586PKG4 -    David M Dalpiaz
Model & Learning in Data SciMLD77586PKG40930 - 1045 F  1320 Digital Computer Laboratory David M Dalpiaz