faculty
Gary Davis, PhD
Professor
Mathematics
Contact
508-999-8739
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Liberal Arts 394E
Teaching
Programs
Programs
- Data Science BS, BS/MS
- Data Science Graduate Certificate
- Data Science MS
- Engineering and Applied Science PhD
- Mathematics BA, BS
Teaching
Courses
A team-based learning experience that gives students the opportunity to synthesize prerequisite course material and to conduct real-world analytics projects using large data sets of diverse types and sources. Students work in independent teams to design, implement, and evaluate an appropriate data integration, analysis, and display system. Oral and written reports and ethical aspects are highlighted.
A team-based learning experience that gives students the opportunity to synthesize prerequisite course material and to conduct real-world analytics projects using large data sets of diverse types and sources. Students work in independent teams to design, implement, and evaluate an appropriate data integration, analysis, and display system. Oral and written reports and ethical aspects are highlighted.
A team-based learning experience that gives students the opportunity to synthesize prerequisite course material and to conduct real-world analytics projects using large data sets of diverse types and sources. Students work in independent teams to design, implement, and evaluate an appropriate data integration, analysis, and display system. Oral and written reports and ethical aspects are highlighted.
Written presentation of an original research topic in Data Science which demonstrates the knowledge & capability to conduct independent research. The thesis shall be completed under the supervision of a faculty advisor. An oral examination in defense is required.
Continuation of MTH 332. Covering topics are advanced mathematical statistics topics, including detailed hypothesis testing, linear models, and regression analysis. This course also covers concepts and selected algorithms in machine learning.
Continuation of MTH 332. Covering topics are advanced mathematical statistics topics, including detailed hypothesis testing, linear models, and regression analysis. This course also covers concepts and selected algorithms in machine learning.
Continuation of MTH 332. Covering topics are advanced mathematical statistics topics, including detailed hypothesis testing, linear models, and regression analysis. This course also covers concepts and selected algorithms in machine learning.
Continuation of MTH 332. Covering topics are advanced mathematical statistics topics, including detailed hypothesis testing, linear models, and regression analysis. This course also covers concepts and selected algorithms in machine learning.
Research
Research interests
- Memory systems
- DEs
- Time series
- Mathematics education
Latest from Gary
Mentioned in
- Mar 25, 2024 McCord Murray '24: The science of math