FIN 550

Spring 2023 Part of Term 1

Part of Term 1
Jan 17-May 3

Big Data Analytics in Finance for Predictive and Causal Analysis

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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 550 if the student has received credit for FIN 510 Big Data Analytics in Finance for Predictive and Causal Analysis (71511, 71512, 71513, 72873, 72874, 72875). Prerequisite: Consent of Instructor.

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FIN 550 class schedule data for spring 2023
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	74065	Lecture-Discussion	BA1	8:00AM -9:20AM	TR	3007 Business Instructional Fac	Diaz Klaassen, F Gao, X	Part of Term: 1 Date Range: 01/17/23-05/03/23 Restriction(s): Restricted to MS: Technology Management-UIUC or MS:Management -UIUC.
	74066	Lecture-Discussion	BA2	9:30AM -10:50AM	TR	3007 Business Instructional Fac	Diaz Klaassen, F Gao, X	Part of Term: 1 Date Range: 01/17/23-05/03/23 Special Approval: Instructor Approval Required Section Info: Registration is contingent upon an admission screening process. Students accepted into the course will be notified by email. Applications may be found online at https://go.gies.illinois.edu/FIN550Apply. Restriction(s): Restricted to MS:Finance -UIUC, MS: Finance Cost Rec -UIUC, MS: Financial Engineering, MS: Finance - UIUC, or MS: Finance Cost Rec - UIUC.