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

Students 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
1 day after enrollment
Transfer Request Deadline
1 day 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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