Fall 2019 - CMPT 741 G100

Data Mining (3)

Class Number: 9023

Delivery Method: In Person

Overview

  • Course Times + Location:

    Tu 12:30 PM – 2:20 PM
    SECB 1012, Burnaby

    Th 1:30 PM – 2:20 PM
    WMC 2202, Burnaby

Description

CALENDAR DESCRIPTION:

The student will learn basic concepts and techniques of data mining. Unlike data management required in traditional database applications, data analysis aims to extract useful patterns, trends and knowledge from raw data for decision support. Such information are implicit in the data and must be mined to be useful.

COURSE DETAILS:

This course introduces data mining, an area that plays a key role in Big Data analytics. The goal of data mining is the efficient discovery of useful patterns in large datasets. This course emphasizes data-driven thinking and focuses on fundamental data mining algorithms and key applications. Students taking this course are expected to have taken an algorithms course and to have an understanding of basic statistics equivalent to an entry-level course. This course will prepare students to conduct their own research in the area of data mining

Topics

  • Introduction
  • Data preprocessing
  • Cluster Analysis
  • Classification
  • Outlier Analysis
  • Frequent Pattern Mining
  • Social Network Analysis
  • Recommender systems

Grading

NOTES:

The grading scheme will be discussed in the first week of the class. Evaluation will be based on paper and pencil assignments, a course project, and a (midterm or final) exam.

Materials

REQUIRED READING:

Data Mining: The Textbook
Charu Aggarwal
Springer
2015
ISBN: 9783319141411

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS