Data Mining from University of Louisville

Data Mining

This module provides an overview of basic concepts in data mining and main methodologies and approaches used for knowledge discovery from data. Topics include the definition of data mining field; data mining process; data preprocessing; predictive and descriptive data mining; evaluation of data mining models; and privacy and security of data. The?module?uses?case studies?from healthcare?applications.

Course Overview

Overall Proficiency Level

1 - Basic

Course Prerequisites

None

Training Purpose

Skill Development

Specific Audience

All

Delivery Method

Online, Instructor-Led

Online, Self-Paced

Online, Instructor-Led
Online, Self-Paced

Learning Objectives

During the course we will try to answer some of the following questions emphasizing the techniques and methodologies developed to support research, development, and applications in this new field. What is data mining? Why data mining: motivation and benefits? What kind of data to mine? When to mine the data? How to organize the mining process? What are challenges in data mining?

Framework Connections

Implementation and Operation

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Competency Areas

Cyber Resiliency

Work Roles

Data Analysis

Feedback

If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.