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.
3.00 credits | May be repeated for a total of 3 credits.
Prerequisites: Recommended preparation: a course in introductory linear algebra and introductory statistics.
Grading Basis: Graded
Develop proficiency in fundamental data analytic techniques in the R scripting language commonly used in environmental science and engineering with applications spanning practice and research. Topics include: trend detection, numerical approaches to model fitting, cluster analysis, and introductory machine learning methods.
No classes found.