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IS 507 AO - Data, Stat, Info

Campus: Urbana-Champaign

Description:

An introduction to statistical and probabilistic models as they pertain to quantifying information, assessing information quality, and principled application of information to decision making, with focus on model selection and gauging model quality. The course reviews relevant results from probability theory, parametric and non-parametric predictive models, as well as extensions of these models for unsupervised learning. Applications of statistical and probabilistic models to tasks in information management (e.g. prediction, ranking, and data reduction) are emphasized. Course Information: 4 graduate hours. No professional credit. Prerequisite: Graduate standing.

Special Instructions:

Graduate student questions may be sent to ischool-advising@illinois.edu

Academic Program Restrictions:

MS:Information Management-UIUC

Option 1

Number of Required Visit(s): 0

Course Level: Graduate

Credit: 4

Term(s): Fall


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