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Learning Outcomes

1.
Be able to apply advanced business sensibilities to real-world problems involving complex data sets.
  • Professionals
  • Scholars
2.
Be able to apply the highest ethical standards to their professional and personal lives.
  • Professionals
  • Global Citizens
3.
Be able to prepare, process, interpret and present data using appropriate qualitative and quantitative techniques.
  • Scholars
  • Professionals
4.
Demonstrate knowledge and skills in formulating problems involving both qualitative and quantitative data.
  • Professionals
  • Scholars
5.
Demonstrate an advanced working knowledge of scientific criteria and methods of investigation, and a concern for objectivity and precision.
  • Professionals
  • Global Citizens

Graduate Capabilities

For more information on Graduate Capabilities please click on this link

Available in Program(s)
Single degree program(s) in which this specialisation is available:

Master of Data Science and Decisions - MDataSci8959 - Data Science and Decisions

Specialisation Structure
30 Units of Credit:

Students must complete 30 UOC.

Core Courses

Students must take 24 UOC of the following courses.

ECON6202
6 UOC
Policy Evaluation Methods
ECON6312
6 UOC
Policy Applications of Behavioural Economics
ECON6313
6 UOC
Public Economics and Regulation

Prescribed Electives

Students must take at least 6 UOC of the following courses.

COMP6714
6 UOC
Information Retrieval and Web Search
COMP9024
6 UOC
Data Structures and Algorithms
COMP9313
6 UOC
Big Data Management
ECON5206
6 UOC
Financial Econometrics
ECON5324
6 UOC
Behavioural Economics
ECON6307
6 UOC
Health Economics
ECON6310
6 UOC
Experimental and Behavioural Economics
ECON6313
6 UOC
Public Economics and Regulation
FINS5548
6 UOC
Financial Technology
FINS5555
6 UOC
Behavioural Approaches in Finance
INFS5700
6 UOC
Introduction to Business Analytics
INFS5831
6 UOC
Information Systems Consulting
MARK5822
6 UOC
Marketing Analytics in a Big Data World
MATH5165
6 UOC
Optimization
MATH5171
6 UOC
Linear and Discrete Optimization Modelling
MATH5425
6 UOC
Graph Theory
MATH5806
6 UOC
Applied Regression Analysis
MATH5836
6 UOC
Data Mining and its Business Applications

Enrolment Disclaimer

Please note that this Handbook is a comprehensive catalogue of our offerings and includes courses that can be taken to satisfy program requirements irrespective as to their availability for a particular year. Availability of courses is best checked using filters on this site or on the class timetable site.

You are responsible for ensuring that you enrol in courses according to your program requirements and by following the advice of your Program Authority. myUNSW enrolment checks that you have met enrolment requirements such as pre-requisites for individual courses but not that you are enrolling in courses that will count towards your program requirements.

Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)
Pre-2019 Handbook Editions