• Online, Self-Paced
Course Description

Nestled within machine learning are ensemble techniques that enable the combination of multiple models to reduce prediction error and improve forecasting ability. Explore machine learning methods, including random forests and uplift models.

Learning Objectives

Random Forests

  • Start the course
  • identify key features of random forests
  • identify key features of decision trees
  • recognize random forest performance measurements
  • identify key random forest model concepts

Uplift Models

  • identify key features of uplift models
  • recognize who to target with uplift models
  • recognize how uplift models work

Practice: Advanced Predictive Tools

  • implement a random forest and an uplift model using an example dataset

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • All-Source Analysis
  • Data Administration
  • Systems Analysis