IDSC 4444: Descriptive and Predictive Analytics

2 Credits

Descriptive and Predictive Analytics exposes students to a number of data mining and machine learning methods, including: exploratory methods (such as association rules and cluster analysis), predictive methods (such as K-NN and decision trees), and text mining methods. The course combines theoretical lectures with lab lectures, where the methods are practically implemented using the software R. prereqs: IDSC 3001; non-MIS majors also need IDSC 4110

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All Instructors

B+ Average (3.473)Most Common: A (39%)

This total also includes data from semesters with unknown instructors.

1385 students
SNWFDCBA
  • 4.01

    /5

    Recommend
  • 3.99

    /5

    Effort
  • 4.22

    /5

    Understanding
  • 3.96

    /5

    Interesting
  • 4.25

    /5

    Activities


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