• Online, Instructor-Led
  • Online, Self-Paced
Course Description

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.

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

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

Specialty Areas

  • Cyber Defense Analysis
  • Cyber Investigation
  • Collection Operations
  • Cybersecurity Management
  • Training, Education, and Awareness

Specialty Areas have been removed from the NICE Framework. With the recent release of the new NICE Framework data, updates to courses are underway. Until this course can be updated, this historical information is provided to give better context as to how it can help you with your cybersecurity goals.

Feedback

If you would like to provide feedback for this course, please e-mail the NICCS SO at NICCS@hq.dhs.gov.