Table A - Data Analytics for Business

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).

Please note. The following table lists Table A units for the specialsiation only. For details of the Table A - Core, Table - Foundational, Table A - Capstone, Table A Selective and Table A Elective units of study, please refer to Table A for the Graduate Certificate, Graduate Diploma and Master of Commerce or Table A for the Master of Commerce (Extension) sections in this handbook.

Unit outlines will be available through Find a unit outline two weeks before the first day of teaching for 1000-level and 5000-level units, or one week before the first day of teaching for all other units.
 

Errata
Item Errata Date
1.

The following unit was omitted from the table. It is available as a selective unit for the Data Analytics in Business specialisation. It will be available in Semester 1.

MKTG6010 Machine Learning in Marketing
Credit points: 6 Session: Semester 1 Classes: Refer to the unit of study outline https://www.sydney.edu.au/units Prerequisites: BUSS6002 Assessment: Refer to the unit of study outline https://www.sydney.edu.au/units

25/1/2021
2.

The following unit has been cancelled for Semester 1, 2021. It will continue to be offered for Semester 2.

MKTG6018 Customer Analytics and Relationship Management

25/1/2021
3.

The following unit was omitted from the table. It is available as a selective unit for the Data Analytics in Business specialisation. It will be available in Semester 1.

MKTG6999 Customer Social Data Analytical Tools
Credit points: 6 Session: Semester 2 Classes: Refer to the unit of study outline https://www.sydney.edu.au/units Prerequisites: BUSS6002 Prohibitions: MKTG6998 Assumed knowledge: Python programming, as covered in BUSS6002. Assessment: Refer to the unit of study outline https://www.sydney.edu.au/units
25/1/2021
4.

Prerequisites and Corequisites have changed for the following unit. They now read:

QBUS6810 Statistical Learning and Data Mining 
Prerequisites:
ECMT5001 or QBUS5001 Corequisites: BUSS6002

1/2/2021
Unit of study Credit points A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition Session

Data Analytics for Business

Achievement of a specialisation in Data Analytics for Business requires a minimum of 30 credit points from this table comprising:
(i) 6 credit points of Table A - Foundational units of study*
(ii) 6 credit points of Table A - Data Analytics for Business core units of study; and
(iii) 18 credit points of Table A - Data Analytics for Business selective units of study.
Students completing this specialisation to meet the requirements for the Master of Commerce or as their compulsory specialisation for the Master of Commerce (Extension) must complete a 6 credit point capstone unit related to the specialisation from Table A - Capstone units of study section in Table A for the Graduate Certificate, Graduate Diploma and Master of Commerce OR Table A for the Master of Commerce (Extension).
Students completing this specialisation as an optional second specialisation for the Master of Commerce (Extension) do not need to complete a capstone unit.

Units of study

The units of study are listed below.

Table A - Foundational unit of study*

* Note. Foundational units count towards both the Foundational units of study for the course and the specialisation.
QBUS5001
Foundation in Data Analytics 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


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
Semester 2

Table A - Data Analytics for Business

Core units of study
BUSS6002
Data Science in Business
6    A Basic knowledge of probability and statistics
C QBUS5001 or QBUS5002


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
Semester 2
Selective units of study
INFS6018
Managing with Information and Data
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.
C INFS5002 or COMP5206 or QBUS5001


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
INFS6023
Data Visualisation For Managers
6   

Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
INFS6024
Managing Data at Scale
6      Semester 2
ITLS6111
Spatial Analytics
6    A Basic knowledge of Excel is assumed.
N ITLS6107 or TPTM6180


This unit will use R programming language to perform statistical analyses and spatial analyses. No prior programming knowledge is required.
Semester 2
MKTG6010
Machine Learning in Marketing
6    P BUSS6002
Semester 1
MKTG6018
Customer Analytics and Relationship Management
6   

Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
Semester 2
MKTG6999
Customer Social Data Analytical Tools
6    A Python programming, as covered in BUSS6002.
P BUSS6002
N MKTG6998


Note. This unit uses Python programming. The related unit of study MKTG6998 will examine social media data from angles without the need for Python programming.
Semester 2
QBUS6310
Business Operations Analysis
6    P ECMT5001 or QBUS5001 or QBUS5002
N ECMT6008


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 2
QBUS6810
Statistical Learning and Data Mining
6    P ECMT5001 or QBUS5001 or BUSS6002


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
Semester 2
QBUS6820
Business Risk Management
6    A Knowledge of basic probability theory and familiarity with spreadsheet modelling
P ECMT5001 or QBUS5001


Refer to the unit of study outline https://www.sydney.edu.au/units
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


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
Semester 2
QBUS6840
Predictive Analytics
6    P (QBUS5001 or ECMT5001) and BUSS6002


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
Semester 2
QBUS6850
Machine Learning for Business
6    P QBUS6810


Refer to the unit of study outline https://www.sydney.edu.au/units
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


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
Semester 2