CPSC 4830: Data Mining for Data Analytics
| Course Format | Lecture 2.0 h + Seminar 0.0 h + Lab. 2.0 h |
| Credits | 3.0 |
Course Description
Once data has been gathered, it must be cleaned, processed, and analyzed in order to find the most appropriate model to describe the underlying data. Using text classification and anomaly detection, students identify and implement the phases of a data mining process to mine and extract frequent pattern and outliers within data.
Students will receive credit for only one of CPSC 4160 or 4830.
Registration in this course is restricted to students admitted to the Post-Degree Diploma in Data Analytics.
Prerequisite(s): A minimum "C" grade in one of CPSC 4810 or 4820; and both DANA 4810, and 4820.
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