Graduate Course Descriptions

The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.

6615. Statistical Learning and Optimization

Also offered as: STAT 6615

3.00 credits

Prerequisites: Instructor consent and intermediate courses in mathematical and applied statistics.

Grading Basis: Graded

Computationally intensive statistical learning methods with optimization techniques: classification, discriminant analysis, (generalized) additive models, boosting, regression trees, regularized regression, principal components, support vector machines, and (deep) neural networks.

No classes found.