Detailed Course Information

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MAT 343 - Explorations in Data Analytics
Explorations in Data Analytics Prerequisite: MAT 342 This course covers advanced analytical techniques students can use in the modeling and evaluation stages of a data science project. Such techniques may include neural networks, k-means and model-based clustering, association rules, segmentation models, and model voting techniques. This course relies on the foundational structure and methodologies established in Explorations in Data Science (MAT 342). Students will complete a group analysis of a data set and present their findings in a lightning talk. Soft skills such as communication and teamwork are built alongside analytical skills. 3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Mathematical Sciences Department Prerequisites: MAT 342

MAT 343 - Explorations in Data Analytics

Explorations in Data Analytics
Prerequisite: MAT 342

This course covers advanced analytical techniques students can use in the modeling and evaluation stages of a data science project. Such techniques may include neural networks, k-means and model-based clustering, association rules, segmentation models, and model voting techniques. This course relies on the foundational structure and methodologies established in Explorations in Data Science (MAT 342). Students will complete a group analysis of a data set and present their findings in a lightning talk. Soft skills such as communication and teamwork are built alongside analytical skills.

3.000 Credit hours
3.000 Lecture hours

Levels: Undergraduate
Schedule Types: Lecture

Mathematical Sciences Department

Prerequisites:
MAT 342

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Detailed Course Information		Current Aug 26, 2026