Business Analytics
Errata
| item | Errata | Date |
|---|---|---|
| 1. |
The prerequisities have changed for the following unit. They now read: QBUS6810 Statistical Learning and Data Mining P (ECMT5001 or QBUS5001) and BUSS6002. |
31/01/2020 |
| 2. |
The prerequisities have changed for the following unit for 2020 only. They now read: QBUS6810 Statistical Learning and Data Mining P ECMT5001 or QBUS5001 or BUSS6002 |
20/08/2020 |
The units of study listed in the following table are those available for the current year. Students may also include any units of study, which are additional to those currently listed, which appear under these subject areas in the Business School handbook/website in subsequent years (subject to any prerequisite or prohibition rules).
Table of postgraduate units of study: Commerce
| Unit of study | Credit points | A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition | Session |
|---|---|---|---|
Business Analytics |
|||
| Achievement of a specialisation in Business Analytics requires 30 credit points from this table comprising: | |||
| (i) 6 credit points in foundational units of study | |||
| (ii) 24 credit points in elective units of study. | |||
Units of study for the specialisation |
|||
Foundational unit of study |
|||
| QBUS5001 Quantitative Methods for Business |
6 | A Students should be capable of reading data in tabulated form and working with Microsoft EXCEL and doing High School level of mathematics N ECMT5001 or QBUS5002 |
Semester 1 Semester 2 |
Elective units of study |
|||
| BUSS6002 Data Science in Business |
6 | A Basic knowledge of statistics, probability and linear algebra P QBUS5001 or QBUS5002 |
Semester 1 Semester 2 |
| INFS6018 Managing Business Intelligence |
6 | A Understanding the major functions of a business and how those business functions interact internally and externally so the company can be competitive in a changing market. How information systems can be used and managed in a business. How to critically analyse a business and determine its options for transformation. (ii) Desirable Experience as a member of a project team. |
Semester 1 |
| QBUS6310 Business Operations Analysis |
6 | P ECMT5001 or QBUS5001 or QBUS5002 N ECMT6008 |
Semester 2 |
| QBUS6320 Management Decision Making |
6 | A Basic Algebra, Probability, and Statistics P QBUS5001 or QBUS5002 |
Semester 1 |
| QBUS6810 Statistical Learning and Data Mining |
6 | P BUSS6002 |
Semester 1 Semester 2 |
| QBUS6820 Business Risk Management |
6 | A Knowledge of basic probability theory and familiarity with spreadsheet modelling P ECMT5001 or QBUS5001 |
Semester 2 |
| QBUS6830 Financial Time Series and Forecasting |
6 | A Basic knowledge of quantitative methods including statistics, basic probability theory, and introductory regression analysis. P ECMT5001 or QBUS5001 |
Semester 1 Semester 2 |
| QBUS6840 Predictive Analytics |
6 | P (QBUS5001 or ECMT5001) and BUSS6002 |
Semester 1 Semester 2 |
| QBUS6850 Machine Learning for Business |
6 | P QBUS6810 |
Semester 1 Semester 2 |
| QBUS6860 Visual Data Analytics |
6 | A The unit assumes knowledge of statistics and confidence in working with data. P QBUS5001 or QBUS5002 |
Semester 1 Semester 2 |