School of Information Studies
Page tree




Course Description

Introduction to data mining techniques, familiarity with particular real- world applications, challenges involved in these applications, and future directions of the field. Hands-on experience with open-source software packages. 

Credit(s)

3.0

Prerequisite

IST 687. Exceptions maybe given to students who have acquired skills equivalent to what is taught in IST 687. 

Professor of Record

Steve Wallace

Audience

Graduate students

Learning Objectives

After taking this course, students will be able to: 

  1. Document, analyze, and translate data mining needs into technical designs and solutions.
  2. Apply data mining concepts, algorithms, and evaluation methods to real-world problems.
  3. Employ data storytelling and dive into the data, find useful patterns, and articulate what patterns have been found, how they are found, and why they are valuable and trustworthy.

Course Syllabus

IST 687 Fall 2020 Syllabus- Lin, Ying

IST 687 Fall 2020 Syllabus- Cases, Jesse


Other iSchool Courses