Detailed Course Information |
Spring 2019 Semester
Dec 08, 2019 |
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| HINF 6500 - Predictive Analytics and Modeling |
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Seeks to train students to transform data to useful, actionable knowledge through the use of mathematical and computational models. Reviews popular techniques for data mining and health analytics based on regression and machine-learning methodologies. Introduces students to a spectrum of models—ranging from data-driven to principle-based, mechanistic approaches—and examines how to compare models and use them to improve understanding of data. Introduces model-based methods of artificial intelligence as applied to healthcare problems, covering fundamental principles of AI and a variety of applications in healthcare.
3.000 Credit hours 3.000 Lecture hours Levels: Graduate Schedule Types: Lecture Health Informatics Department Course Attributes: GSBV Bouve Restrictions: Must be enrolled in one of the following Levels: Graduate Prerequisites: Graduate level HINF 6400 Minimum Grade of C- and Graduate level DA 5030 Minimum Grade of C- and Graduate level PPUA 5301 Minimum Grade of C- |
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