CS484
Data Mining(Summer 2023)

Meeting Time and Location:
10:30 pm - 12:35 pm TR ONLINE BLACKBOARD Collaborative (mymasonportal.gmu.edu) Attendance to the lectures is mandatory.

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

Graduate TA: TBA

Course Home Page
CS584

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

Course Outcomes:

The ability to apply computing principles, probability and statistics relevant to the data mining discipline to analyze data.
A thorough understanding of model programming with data mining tools, algorithms for estimation, prediction, and pattern discovery.
The ability to analyze a problem, identifying and defining the computing requirements appropriate to its solution: data collection and preparation, functional requirements, selection of models and prediction algorithms, software, and performance evaluation.
The ability to understand performance metrics used in the data mining field to interpret the results of applying an algorithm or model, to compare methods and to reach conclusions about data.
The ability to communicate effectively to an audience the steps and results followed in solving a data mining problem (through a term project)

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.

Textbook

Data Mining: Introduction to Data Mining by Tan, Steinbach and Kumar

Class Attendance
Required. Please arrive on time. I expect to start at 10:30 sharp; Please participate in class! Ask questions if there is something you don't understand.
Grading Policies

Exams: 45% (quizzes - unnanounced, in class- 30%, Final 15%). Cannot make up missed quizzes!
Assignments: 45%
Participation (activities): 10%

Office hours: By appointment (they will be online, EMAIL ME TO REQUEST ONE)

TA: Ridwan Hossain Talukder mtalukd AT gmu DOT edu
TA office hours: Monday: 10 am - 12 pm (Online) Zoom Link: https://gmu.zoom.us/j/96324951618
Announcements:

Late Policy
Late homework will be accepted with a penalty of 20% per day within 2 days after deadlines and will not be accepted three days after due, unless under prearranged conditions.
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 Code. Any 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

Disability

CS484 Data Mining(Summer 2023)

Announcements:

CS484
Data Mining(Summer 2023)