Detailed Course Information |
Fall 2020
Apr 26, 2024 |
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| CSCI 452 - Data Mining |
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An introduction to data mining, including data cleaning, the application of statistical and machine learning techniques to discover patterns in data, and the analysis of the quality and meaning of results. Machine learning topics may include algorithms for discovering association rules, classification, prediction, and clustering. Lab assignments provide practice applying specific techniques and analyzing results. An independent project provides students with the opportunity to guide a project from data selection and cleaning through to presentation of results. Pre-req: C- or higher in CSCI 366 and MATH 235 or 333 or 335.
4.000 Credit hours 4.000 Lecture hours Levels: Undergraduate Schedule Types: Individual Instruction, Lecture Science and Mathematics Division Computer Science Department Prerequisites: Undergraduate level CSCI 366 Minimum Grade of C- and (Undergraduate level MATH 235 Minimum Grade of C- or Undergraduate level MATH 333 Minimum Grade of C- or Undergraduate level MATH 335 Minimum Grade of C-) |
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