Detailed Course Information |
Fall 2020
Apr 26, 2024 |
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| CSCI 453 - Lg Scale Data Analytics & Viz |
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A practical introduction to data analytics, visualization, and blending theory. Students will learn about and apply various clustering algorithms and techniques for dealing with noisy data, use a distributed data analytics framework, complete laboratory assignments using version control, and enforce reproducibility by having all science easily sharable. Students will become familiar with modern data analytics methods and explore real-world data sets. Visualization of results will be a large component of the course through interactive and static frameworks. 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 Restrictions: May not be enrolled as the following Classifications: Continuing Education Prerequisites: Undergraduate level CSCI 366 Minimum Grade of D- and (Undergraduate level MATH 235 Minimum Grade of D- or Undergraduate level MATH 333 Minimum Grade of D- or Undergraduate level MATH 335 Minimum Grade of D-) |
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