Data Mining(Spring 2018)

Meeting Time and Location:
4:30 pm - 7:10 pm , Innovation Hall 206

Instructor: Prof. Daniel Barbará.
Email: dbarbara (at) gmu (dot) edu
Office: Eng. Bldg 4420
Office hour: by appointment


Course Home Page

This course provides an introduction to the fundamental concepts in Data Mining

Course Outcomes:

Prerequisites: grade of C or better in CS 310 and STAT 344, or permission of instructor Students not satisfying the prerequisites will be dropped from the class.


Class Attendance
Required.  Please arrive on time.  I expect to start at 4:30 sharp; Please participate in class! Ask questions if there is something you don't understand.

Grading Policies
There will also be written homeworks, a final project, a in-class midterm exam, and a final exam. Both the final and midterm are open-book and open-notes. The final exam will be comprehensive, i.e., it will cover the entire course. Missed exams must be arranged with the instructor BEFORE the exam.  Documentation of the illness (doctor's note) is required.  No early exams will be given and make-up exams are strongly discouraged.

End-of-semester numeric scores will be weighted as follows (tentative plan):
  • 40% Assignments
  • 30% Exams (Quizes)
  • 30% project
In order to obtain an A, your final score should be at least 90. A total score of 49 or less will result in an F.

Late Policy

Late homework will be accepted with a penalty of 20% per day within 3 days after deadlines and will not be accepted three days after due, unless under prearranged conditions.

No smartphones, LAPTOPS, TABLETS, or recorders allowed in class. Lectures cannot be recorded without special permission

Honor Code
You are expected to abide by the honor code.  All assignments and exams are individual efforts. Please refer to GMU Academic Policies and Computer Science Department Honor CodeAny violation of the honor code will result in a zero of the assignment/exam, and may result in an F for the class.

School Calendar