Course Overview

This resource introduces participants to concepts and practices common in data mining using the CRISP-DM methodology. It is intended for students and business professionals who are interested in using information systems and technologies to solve organizational problems by mining data, but who may not have a background in computer science. Participants will learn the concepts and techniques required to successfully mine data in RapidMiner and R.

What You'll Learn

  • Introduction to Data Mining and CRISP-DM
  • Organizational Understanding and Data Understanding
  • Data Preparation
  • Correlational Methods - Association Rules
  • k-Means Clustering
  • Discriminant Analysis, k-Nearest Neighbors and Naïve Bayes
  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Neural Networks
  • Text Mining
  • Evaluation and Deployment
  • Data Mining Ethics

Who Should Attend

  • Managers
  • Support Staff
  • Executives
  • Line Managers
  • Supervisors
  • Recent Graduates
  • Business Students
  • CEU Seekers
  • Career Pivoter
  • Resume Builders

Additional Information

Participants must complete all sections to earn the Digital Badge of Completion.
Enroll Now - Select a section to enroll in
Section Schedule
Date and Time TBA
Delivery Options
Course Fee(s)
Fee non-credit $599.00
Drop Request Deadline
No drop request allowed after enrollment
Transfer Request Deadline
No transfer request allowed after enrollment
Section Notes

This is a self-paced course and you will have 365 days to complete after enrollment.

This course is offered through Anderson School of Management.

UNM Staff, Faculty and Retirees can use their Tuition Remission benefit on professional development programs.

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