Graduate

Courses

Computer Science

B565 Data Mining

Credits: 3

Prerequisite(s):

Algorithmic and practical aspects of discovering patterns and relationships in large databases. The course also provides hands-on experience in data analysis, clustering and prediction. Topics include: data preprocessing and exploration, data warehousing, association rule mining, classification and regression, clustering, anomaly detection, human factors and social issues in data mining.

Fall 2017


Instructor: Mehmet Dalkilic
Time: 11:15AM-12:30PM Tue, Thu
Location: GA0001

  • Course History

      Spring 2017


      Instructor: Christopher Raphael
      Time: 4:00PM-5:15PM Tue, Thu
      Location: Ballantine Hall, Room 109

      Fall 2016


      Instructor: Mehmet Dalkilic
      Time: 11:15AM-12:30PM Tue, Thu
      Location: FA102

      Spring 2016


      Instructor: Predrag Radivojac
      Time: 5:45PM-7:00PM Tue, Thu
      Location: Woodburn Hall, Room 120

      Fall 2015


      Instructor: Mehmet Dalkilic
      Time: Multiple Times
      Location: Lindley Hall, Room 008

      Spring 2015


      Instructor: Mehmet Dalkilic
      Time: Multiple Times
      Location: Multiple Locations

      Fall 2013


      Instructor: Mehmet Dalkilic
      Time: Multiple Times
      Location: Lindley Hall, Room 008

      Fall 2012


      Instructor: Mehmet Dalkilic
      Time: 4:00PM-5:15PM Tue, Thu
      Location: Informatics East, Room 130

      Spring 2012


      Instructor: Mehmet Dalkilic
      Time: 1:00PM-2:15PM Mon, Wed
      Location: Informatics East, Room 130