FIN 510

Fall 2021 All Classes

All Classes

Big Data Analytics in Finance for Predictive and Causal Analysis

SHOW FINAL EXAM SCHEDULE

Credit: 4 hours.

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.

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.

My Favorites

My Schedule

Section Status updates every 10 minutes.

FIN 510 class schedule data for fall 2021
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
72875	Lecture-Discussion	BD1	11:00AM -12:20PM	MW	3039 Business Instructional Fac	Molitor, D	Part of Term: 1 Date Range: 08/23/21-12/08/21 Section Info: Recent trends in "big data" present both enormous challenges and opportunities for businesses. This course introduces concepts and techniques of business data analytics and shows how they can be used for making predictions and to distinguish between correlation and causation. 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. Reserved for MSF and MSFE. Restriction(s): Restricted to MS: Financial Engineering or MS: Finance Cost Rec - UIUC.
72873	Lecture-Discussion	BD2	9:30AM -10:50AM	MW	3039 Business Instructional Fac	Gao, X	Part of Term: 1 Date Range: 08/23/21-12/08/21 Section Info: Recent trends in "big data" present both enormous challenges and opportunities for businesses. This course introduces concepts and techniques of business data analytics and shows how they can be used for making predictions and to distinguish between correlation and causation. 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. Restricted to MS: Business Analytics Restriction(s): Restricted to MS:Business Analytics - UIUC.
72874	Online	XD1	11:00AM -12:20PM	MW	n.a.	Molitor, D	Part of Term: 1 Date Range: 08/23/21-12/08/21 Special Approval: Departmental Approval Required Section Info: This online section is only for students registered in-absentia Restriction(s): Restricted to MS:Finance -UIUC, MS: Finance Cost Rec -UIUC, MS: Financial Engineering, MS: Finance - UIUC, or MS: Finance Cost Rec - UIUC.