Course Overview

In today's rapidly changing information technology environment, organizations are using a variety of technologies and tools to create machine learning environments and perform data analytics. This course covers a practical introduction to the process of performing exploratory data analytics to creating machine learning pipelines using a combination of Tableau, Excel, and Azure ML Studio.

What You'll Learn

  • Chapter 1: Introduction to Data Mining
  • Chapter 2: Data Mining Project Methodology
  • Chapter 3: Visualization: Theory and Design
  • Chapter 4: Tableau: Core Features
  • Chapter 5: Tableau: Exploratory Data Analysis
  • Chapter 6: Tableau: JavaScript API
  • Chapter 7: Excel: Multivariate Prediction
  • Chapter 8: ML Studio: Introduction to Pipelines
  • Chapter 9: ML Studio: Data Cleaning and Preparation
  • Chapter 10: ML Studio: Selecting the Features
  • Chapter 11: Modeling: Algorithm Selection
  • Chapter 12: ML Studio: Optimizing Model Fit and Performance
  • Chapter 13: ML Studio: Text Analytics
  • Chapter 14: Modeling: Recommendation Engines
  • Chapter 15: Project: Putting It All Together

Who Should Attend

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

Additional Information

Participant must complete all sections to earn 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 class 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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