96324 - Data Analytics and Machine Learning Applications
6721245
Delivery Options
Online Self-Paced
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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.
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This course is offered through The James & Gail Ellis School of Business Leadership.
UNM Staff, Faculty and Retirees can use their Tuition Remission benefit on professional development programs.
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