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
Web Page
Course Director
Title | Section | CRN | Type | Hours | Times | Days | Location | Instructor |
---|---|---|---|---|---|---|---|---|
Model & Learning in Data Sci | MLD | 77586 | PKG | 4 | - | David M Dalpiaz | ||
Model & Learning in Data Sci | MLD | 77586 | PKG | 4 | 0930 - 1045 | F | 1320 Digital Computer Laboratory | David M Dalpiaz |