Course

Course Summary
Credit Type:
Course
ACE ID:
AICP-0149
Organization's ID:
AIDA 181
Location:
Classroom-based
Length:
7 weeks (14 hours)
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Upper-Division Baccalaureate 4 Enterprise Risk Management or Actuarial Science
Description

Objective:

The course objective is to enable the student to understand the basics of predictive modeling and the application of big data analysis techniques to claims, underwriting, and risk management.

Learning Outcomes:

  • Explain basic predictive modeling terminology and concepts and will be able to describe how various big data techniques, such as classification, clustering, regression, text mining, and social network analysis are applied to claims, underwriting, and ri

General Topics:

  • Exploring big data analytics
  • Predictive modeling concepts
  • Big data analysis techniques
  • Underwriting applications of big data analytics
  • Claims applications of big data analytics
  • Risk management applications of big data analytics
  • Implementing a data analytics strategy
Instruction & Assessment

Instructional Strategies:

  • Case Studies
  • Practical Exercises

Methods of Assessment:

  • Examinations

Minimum Passing Score:

70%
Supplemental Materials