MAF759 - Financial Data Analytics
| Year: | 2023 unit information |
|---|---|
| Enrolment modes: | Trimester 1: Burwood (Melbourne), Online |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Cohort rule: | Must be enrolled in courses M530, M535, M630, M720, M740, M750, M755, M770, M794 or D712 |
| Prerequisite: | Nil |
| Corequisite: | Nil |
| Incompatible with: | MAF904 |
| Study commitment | Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit. |
| Scheduled learning activities - campus | 1 x 3 hour seminar per week |
| Scheduled learning activities - online | Online independent and collaborative learning activities including 1 x 1 hour weekly scheduled online seminar |
Content
This unit will enable students to understand the fundamental data analytical methods and tools used in finance. It introduces financial mathematical concepts, statistics and econometrics that are essential tools for financial data analytics. In addition, the unit covers an introduction of machine learning and big data as well as numerical techniques and data visualisation skills using Excel and Tableau to facilitate practical business decision making.
Hurdle requirement
Hurdle requirement: achieve at least 50% of the marks available on the end-of-unit assessment to evidence a minimum proficiency in the aligned finance discipline learning outcomes included in this unit.
Unit Fee Information
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