Instructor: Dr. Daniel Barbará
Description: This course covers the principles of MapReduce and their use to scale Data Mining algorithms
Prerequisites: An undergraduate (or graduate) Data Mining Course. A solid background in Java programming and Python. In order to be able to work on the programming projects, the students must be comfortable with the Java programming language.
Meeting Times and Locations:
Course Web Page: http://cs.gmu.edu/~dbarbara/CS795/index.html
Course Outcomes: At the end of this course, you will
No early exams will be given and make-up exams are strongly
Assignments will be collected
on the date indicated in class. Late submissions will be penalized at 15% each day, and will not be allowed after 3 days of the due date.
GMU Honor Code will be enforced. The students are supposed to work individually on the assignments/projects, unless told otherwise. We reserve the right to use MOSS to detect plagiarism. Violations of GMU Honor Code or a total score of 49 (or less) will result in an F.
No smartphones, laptops, or recorders allowed in class. Lectures cannot be recorded without special permission from the instructor
Computer Accounts: All students should have accounts on the central Mason Unix system mason.gmu.edu (also known as osf1.gmu.edu) and on IT&E Unix cluster zeus.ite.gmu.edu (Instructions and related links are here). Students can work in IT&E computer labs for programming projects during the specified hours.
Students with Disabilities: If you have a documented learning disability or other condition that may affect academic performance you should: 1) make sure this documentation is on file with the Office of Disability Services (SUB I, Rm. 222; 993-2474; www.gmu.edu/student/drc) to determine the accommodations you need; and 2) talk with me to discuss your accommodation needs.
a>) to determine the accommodations you need; and 2) talk with me to discuss your accommodation needs.