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CS 307 - Model & Learning in Data Sci
Last offered Fall 2025
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.
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| Title | Section | CRN | Type | Hours | Times | Days | Location | Instructor |
|---|---|---|---|---|---|---|---|---|
| Model & Learning in Data Sci | M1 | 77586 | PKG | 4 | 1400 - 1515 | T R | 3039 Campus Instructional Facility | David M Dalpiaz |
| Model & Learning in Data Sci | M1 | 77586 | PKG | 4 | 0930 - 1045 | F | 1320 Digital Computer Laboratory | David M Dalpiaz |
| Model & Learning in Data Sci | M2 | 77587 | PKG | 4 | 1400 - 1515 | T R | 3039 Campus Instructional Facility | David M Dalpiaz |
| Model & Learning in Data Sci | M2 | 77587 | PKG | 4 | 0930 - 1045 | F | 1320 Digital Computer Laboratory | David M Dalpiaz |
| Model & Learning in Data Sci | M3 | 80859 | PKG | 4 | 1100 - 1215 | F | 1320 Digital Computer Laboratory | David M Dalpiaz |
| Model & Learning in Data Sci | M3 | 80859 | PKG | 4 | 1400 - 1515 | T R | 3039 Campus Instructional Facility | David M Dalpiaz |
| Model & Learning in Data Sci | M4 | 80885 | PKG | 4 | - | David M Dalpiaz | ||
| Model & Learning in Data Sci | M4 | 80885 | PKG | 4 | 1100 - 1215 | F | 1320 Digital Computer Laboratory | David M Dalpiaz |