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Master of Business Analytics (MC-BUSANA)
Masters (Coursework)Year: 2023 Delivered: On Campus (Parkville)
About this course
Contact
Melbourne Business School
Currently enrolled students:
Degree Program Services
Email: programservices@mbs.edu
Future students:
Admissions Office
200 Leicester Street
Carlton Victoria 3053 Australia
Tel: 61 3 9349 8200
Email: study@mbs.edu
Academic Director: Dr. Simon Holcombe
Coordinator
Simon Holcombe
Overview
Award title | Master of Business Analytics |
---|---|
Year & campus | 2023 — Parkville |
CRICOS code | 084058J |
Fees information | Subject EFTSL, level, discipline and census date |
Study level & type | Graduate Coursework |
AQF level | 9 |
Credit points | 150 credit points |
Duration | 12 months full-time or 36 months part-time |
The goal of this course is to equip its graduates with the capabilities to apply data analytic techniques to a variety of business problems. The knowledge and skills required to apply data analytic techniques to business problems are multi-disciplinary, drawing on mathematics, statistics, computer science, and business and economics. The course will cover foundation and advanced data analytic techniques, as well as frameworks for applying those techniques to a variety of business contexts.
Entry requirements
1. In order to be considered for entry, applicants must have:
- completed an undergraduate degree of 3 or 4 years minimum in one of the relevant areas listed below, taken at a third-year university level from a recognised institution, with a minimum weighted average mark (WAM) of 65% or equivalent.
o Commerce
o Mathematics and/or Physics
o Computer Science or Information Systems
o Engineering and/or Science
- Interviews will be required for applicants who are shortlisted; and
- Two years of documented working experience for part-time applicants only.
Meeting these requirements does not guarantee selection.
2. In ranking applications, the Selection Committee will consider:
- prior academic performance; and
- an interview for short-listed applicants;
- The work experience (only applicable to part-time applicants)
3. The Selection Committee may seek further information to clarify any aspect of an application in accordance with the Academic Board Rules on the use of selection instruments.
4. Applicants are required to satisfy the university’s English language requirements for graduate courses. For those applicants seeking to meet these requirements by one of the standard tests approved by the Academic Board, performance band 7.0 is required. International students must demonstrate proficiency in English either through IELTS score (minimum score requirement of 7.0 overall with no individual score less than 7) or TOEFL IBT score (minimum of 94, and a written score minimum of 27 and no band less than 24).
Note:
GMAT scores may be required if a University of Melbourne credit average equivalence is difficult to obtain.
Inherent requirements (core participation requirements)
For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry.The University is dedicated to providing support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website. http://www.services.unimelb.edu.au/disability/
Intended learning outcomes
On completion of this course, students should be able to:
- Identify appropriate analytic techniques to address business problems - Students will translate business decision problems into quantitative form. - Students will diagnose a situation and identify appropriate applications of statistical models, data mining and optimisation techniques
- Apply analytical skills and technical methods to develop innovative solutions in business contexts - Students will investigate data structures relevant to business environments and problems - Students will appropriately apply and synthesise key analytics models and techniques to resolve business problems
- Integrate the knowledge and skills acquired to conduct research in an industry setting - Students will appropriately select one or more advanced analytical techniques to apply to a business setting with real data Application of Knowledge and Skills
- Deal with ambiguity and uncertainty - Students will make appropriate judgements about how to proceed in an environment with incomplete information - Students will identify and be able to deal with ambiguities and bias in data
- Communicate the results of technical analysis - Students will display effective verbal communication skills when making a presentation - Students will write reports on data analysis projects which can be understood by non-technical audiences - Students will develop graphs and data visualisations to effectively convey information
- Apply Professional Standards - Students will critically evaluate and apply professional and ethical standards in the analysis of data - Students will reflect on their behaviour in teams and develop strategies to improve
Course structure
Full-time and Part-time – 150 credit pts
Code
Name
Study period
Credit Points
BUSA90539
Business Data Platforms
12.5
Code
Name
Study period
Credit Points
BUSA90537
Coding for Business Problems
12.5
Code
Name
Study period
Credit Points
BUSA90538
Decision Making and Optimisation
12.5
Code
Name
Study period
Credit Points
BUSA90536
Statistical Learning for Business
12.5
Code
Name
Study period
Credit Points
BUSA90542
Machine Learning & AI for Business
12.5
Code
Name
Study period
Credit Points
BUSA90540
Causal Analytics for Business
12.5
Code
Name
Study period
Credit Points
BUSA90541
Predictive Business Analytics
12.5
Code
Name
Study period
Credit Points
BUSA90543
Text Analytics for Business
12.5
Code
Name
Study period
Credit Points
BUSA90544
Marketing Analytics
12.5
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90545 | Supply Chain Analytics |
September (On Campus - Parkville)
October (On Campus - Parkville)
|
12.5 |
Capstone subjects:
Standard pathway
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90546 | Risk Analytics | October (On Campus - Parkville) |
12.5 |
And
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90547 | Applied Business Analytics | Not available in 2023 | 12.5 |
* (part-time)
Or
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90550 | Prof Development & Application I | January (On Campus - Parkville) |
6.25 |
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90551 | Prof Development & Application II | August (On Campus - Parkville) |
6.25 |
* (full-time)
Research pathway
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90504 | Individual Research Project | August (On Campus - Parkville) |
25 |
*Note: Students who would like to take Research Pathway are required to acquire the approval of course coordinator prior to enrolment.
Last updated: 30 January 2024