School of Information Studies
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Course Description

Introduction to data mining techniques, familiarity with particular real-world applications, challenges involved in these applications, and future directions of the field. Optional hands-on experience with commercially available software packages. Meets with IST 707. 

Credit(s)

3.0

Prerequisite

IST 387/687. Exceptions maybe given to students who have acquired skills equivalent to what is taught in IST 387/687.

Professor of Record

Steve Wallace

Audience

Undergraduate (407) & Graduate Students (707). 

Learning Objectives

After taking this course, students will be able to: 

  1. Document, analyze, and translate data analytics needs into technical designs and solutions.
  2. Apply data analytics 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 407/707 Fall 2020 Syllabus


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