• Online, Self-Paced
Course Description

Purposeful information can be extracted from large data sets to determine what has, could, or should happen. Explore descriptive, predictive, and prescriptive analytics, including data mining, distribution models, and hypothesis testing.

Learning Objectives

Data Mining and Analytics

  • start the course
  • recognize key features of descriptive analytics
  • recognize key features of prescriptive analytics
  • recognize key features of data mining
  • identify important data mining concepts and techniques
  • identify data mining methods used for predictive analysis

Data Distributions and Hypothesis Testing

  • identify features of a standard normal distribution
  • list features of the Binomial and Poisson distributions
  • recognize key features of hypothesis testing and its application
  • recognize key features of one and two-tailed hypothesis tests

Practice: Data Mining Methods

  • match analytics problems to appropriate data mining methods

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