George Mason University

DEPARTMENT OF COMPUTER SCIENCE

CS 657 Mining Massive Datasets – Fall 2018

Instructor: Dr. Daniel Barbará

Description: This course covers the principles, techniques, and methods to scale Data Mining algorithms

Prerequisites: CS 584. A solid background in Python. In order to be able to work on the programming projects, the students must be comfortable with the Python programming language.

Meeting Times and Locations:

• Section 001:  Thursdays  4:30-7:10PM  James Buchanan Hall D005
• Engility Section: W 4:30-7:10PM

Readings:
Textbooks:

• Apache Spark, Jeffrey Aven, ISBN: 978-0-672-33851-9
• Machine Learning with Spark, Nick Pentreath, ISBN: 978-1-78328-851-9
• "Mining Massive DataSets" by A. Rajaraman and J. Ullman

Office Hours: : By appointment(Office: Eng. Buldg., Room 4420)

Course Web Page: http://cs.gmu.edu/~dbarbara/CS657/index.html

Course Outcomes: At the end of this course, you will

• Demonstrate knowledge about the role and purpose of the MapReduce, Spark, and other technologies in scaling data mining applications
• Understand the problems inherent to handle massive data sets in data mining

Grading:

• Exam 25%
• Programming Projects 45%
• Final Project 30%

No early exams will be given and make-up exams are strongly discouraged.

Assignments will be submitted in BlackBoard on the date indicated in class. Late submissions will NOT be accepted.
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.