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Data Analytics for Finance and Insurance - ACST890

This unit focuses on the rapidly evolving area of high-performance commercial computing in finance and insurance and its associated `Big Data' and predictive analytics applications. It equips students with the necessary computing and statistical tools to be become active participants in the field. Students will solve `Big Data' problems at the Linux command line, harness the R language to perform data analytics and tease data out of relational databases using SQL. The unit examines statistical learning, and treats a variety of topics, from linear regression to support vector machines that, coupled with computing knowledge, take commercial supercomputing beyond analysing bounced cheques, discovering fraud or managing Facebook friends. The statistics learned will be applied using the R language, and R will also enable the study of various data visualisation applications, which are important to both understanding data and communicating findings.

Credit Points: 4
When Offered:

S1 Evening - Session 1, North Ryde, Evening

Staff Contact(s): Dr Sachi Purcal
Prerequisites:

Admission to MActPrac Prerequisite Information

Corequisites:

NCCW(s):
Unit Designation(s):

Commerce

Assessed As: Graded
Offered By:

Department of Applied Finance and Actuarial Studies

Faculty of Business and Economics

Course structures, including unit offerings, are subject to change.
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