CS 657 Mining Massive Datasets Fall 2024- D. Barbara

CS 657 Mining Massive Datasets Fall 2024

Instructor: Dr. Daniel Barbará

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

Prerequisites: CS 584 (Strictly enforced!.) 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: Thursday 4:30-7:10PM ONLINE.

Readings:
Textbooks:

"Mining Massive DataSets" by A. Rajaraman and J. Ullman 3rd edition
"Large-Scale Data Analytics with Python and Spark 1st Edition" by Isaac Triguero, Mikel Galar
Frank Kane's Taming Big Data with Apache Spark and Python.

Office Hours: : By appointment(virtual)

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 20%
Programming Projects 45%
Final Project 25%
Participation 10%

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

Assignments will be collected on the date indicated in BlackBoard. NO LATE SUBMISSIONS ALLOWED
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.

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.