96324 - Data Analytics and Machine Learning Applications
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.
This course is offered through Anderson School of Management.
UNM Staff, Faculty and Retirees can use their Tuition Remission benefit on professional development programs.