MAT 328 Techniques in Data Science

Analyzing data sets to extract new insights. Acquisition, data mining, storage, and visualization of real world data using scripting and statistical programming languages. Application of standard statistical tools including hypothesis testing, Bayesian analysis, bootstrapping and regression. Classifying and clustering multidimensional data sets via dimensionality reduction and machine learning techniques.

Credits:

4

Hours

4

Offered

Fall-Spring

Prerequisite

MAT 128 or departmental permission.