Basic principles and methods for data analysis and knowledge
discovery. Emphasizes developing basic skills for modeling and
prediction and performance evaluation. Topics include system design;
data quality, preprocessing, and association; event classification;
clustering; biometrics; business intelligence; and mining complex types
Thursday, 4:30-7:10 pm
Planetary Hall 122
Dr. Jessica Lin
Office: Engineering Building 4419
Email: jessica [AT] cs [DOT] gmu [DOT] edu
Office Hours: Wednesday & Thursday 3-4pm
There will be one midterm exam and a final exam covering lectures and readings (both will be in class, closed book). The final exam is comprehensive. Exams must be taken at the scheduled time and place, unless prior arrangement has been made with the instructor. Missed exams cannot be made up.
Honor Code Statement
The GMU Honor Code is in effect at all times. In addition, the CS Department has further honor code policies regarding programming projects, which are detailed here. Any deviation from the GMU or the CS department Honor Code is considered an Honor Code violation. All assignments for this class are individual unless otherwise specified.
If you have a documented learning disability or other condition which may affect academic performance, make sure this documentation is on file with the Office of Disability Services and then discuss with the professor about accommodations.