Big Data – Advanced

This course will provide training on advanced practices and procedures involved with Big Data analysis. The course is intended as a follow-up to the intermediate Big Data course. Participants will learn how to use advanced techniques to deal with complex business problems faced by regulators and businesses alike. The course will cover advanced techniques including geospatial analysis, loess regression, probit regressions, neural networks, and cluster analysis.

Course Objectives

By the end of the course, the participants will be able to:

• Explain how to perform analysis of relational and geographic data using geospatial analysis and cluster analysis
• Use regression techniques to control for unobservable effects
• Use comparative analysis techniques like difference-in-difference analysis
• Apply loess regression to Big Data
• Discuss neural networks, machine learning, and alternative methods of analysis

Suggested Prerequisites:

• Big Data or equivalent Knowledge

Program Level:Advanced

Advance Preparation: Working Knowledge of Excel

Computers and Financial Calculators: Computers

Recommended CPE Credits: 7