Simon Fraser University
Engaging the World

Course Outlines

Spring 2020 - CMPT 459 D100

Special Topics in Database Systems (3)

Data Mining

Class Number: 6741

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 6 – Apr 9, 2020: Tue, 11:30 a.m.–1:20 p.m.
    Burnaby

    Jan 6 – Apr 9, 2020: Thu, 11:30 a.m.–12:20 p.m.
    Burnaby

  • Exam Times + Location:

    Apr 19, 2020
    Sun, 3:30–6:30 p.m.
    Burnaby

  • Prerequisites:

    CMPT 354.

Description

CALENDAR DESCRIPTION:

Current topics in database and information systems depending on faculty and student interest.

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. Programming assignments will be in Python or R, and students are expected to be (or to make themselves) familiar with one of these programming languages.

Topics

  • Introduction
  • Frequent Pattern Mining
  • Cluster Analysis
  • Outlier Analysis
  • Classification
  • 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, programming assignments, and a final exam.

REQUIREMENTS:

Students must attain an overall passing grade on the weighted average of exams in the course in order to obtain a clear pass (C- or better).

Materials

MATERIALS + SUPPLIES:

  • Data Mining: The Textbook, Charu Aggarwal, Springer, 2015, 9783319141411

REQUIRED READING:

  • Data Mining: The Textbook, Charu Aggarwal, Springer, 2015

ISBN: 9783319141411

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