FIN 510 ONL - Big Data Analytics in Finance

Description:

Recent trends in "big data" present both enormous challenges and opportunities for businesses. This course introduces concepts and techniques of data analytics and shows how they can be used for making predictions, and to distinguish between correlation and causation, in the context of financial and economic analysis. Covered tools include data visualization, machine learning, regression analysis, randomized trials, A/B testing, and quasi-experiments. Students will apply these tools using R programming within the Amazon Web Services cloud computing environment. Course Information: 4 graduate hours. No professional credit. Credit is not given for FIN 510 and these sections of FIN 580: Section BD1, (50081); Section BD2, (48173); and Section BD3, (70398). Prerequisite: Consent of Instructor.

Special Instructions:

THIS IS THE ONLINE-ONLY SECTION FOR THIS COURSE.

Academic Program Restrictions:

MS: Financial Engineering

Option 1

Number of Required Visit(s): 0

Course Level: Graduate

Credit: 4

Term(s): Fall