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DS303

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Statistical Learning

School of Business & AnalyticsUndergraduate
GeneralCourse Requisites

Course Title

Statistical Learning

Course Description

The topics that are discussed in this course are: Basic statistical learning methods such as linear regression and classification; resampling methods such as cross-validation and bootstrapping; model selection methods such as subset selection, ridge and lasso regression, and principle component analysis; tree-based methods such as decision trees and random forests; additional topics may include support vector machines and deep learning. Appropriate R packages are used for the aforementioned methods.

CORE: Quantitative Reasoning

Academic Level

Undergraduate

Course Type (Core Curriculum)

CO, COQR

Instructor Consent Required

No

Credits (Min)

4

Repeatable

No

Saint Michael’s is accredited by the New England Commission of Higher Education. The College is a member of the College Board, Vermont Higher Education Council, Association of Vermont Independent Colleges, Association of Catholic Colleges and Universities, Vermont Campus Compact, and Association of Governing Boards of Universities and Colleges.

Saint Michael’s College is committed to equal opportunity. It does not discriminate against students, employees, or applicants for admission or employment, on the basis of race, color, gender, age, national origin, ethnicity, religion, disability, sexual orientation, gender identity, or physical characteristics.

The provisions of this catalog are not to be regarded as an irrevocable contract between the student and the College. The College reserves the right to change its policies without prior notice.

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