CS580 - Data Mining, Summer 2017 (online)

Course Information

Instructor Information

Textbook

Course Goals

Grading Policies

Grading will be based on eight assignments (75%), one quiz (10%) and class participation through three scheduled discussions (15%). The maximum course total is 1000 points. The letter grade will be determined by the following grading scale:
 
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F
950-1000
900-940
870-890
840-860
800-830
770-790
740-760
700-730
670-690
640-660
600-630
0-590

Late assignments will be marked one letter grade down for each 3 days they are late. It is expected that all students will conduct themselves in an honest manner and NEVER claim work which is not their own. Violating this policy will result in a substantial grade penalty or a final grade of F.
 

Course Content (12 units)

  1. Introduction to Data Mining
  2. Data Warehouse and OLAP
  3. Data preprocessing
  4. Data mining knowledge representation
  5. Attribute-oriented analysis
  6. Data mining algorithms: Association rules
  7. Data mining algorithms: Classification
  8. Data mining algorithms: Prediction
  9. Evaluating what's been learned
  10. Mining real data
  11. Clustering
  12. Text and Web Mining