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Master of Business Analytics (MC-BUSANA)
Masters (Coursework)Year: 2022 Delivered: On Campus (Parkville)
About this course
Coordinator
Ujwal Kayande
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
Overview
Award title | Master of Business Analytics |
---|---|
Year & campus | 2022 — 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 |
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 70% 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.
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
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 providingsupport 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
Learning outcomes:
Students who complete this course will be able to:
1. Identify appropriate data analytic techniques to address business problems.
2. Apply data analytic techniques to solve problems in a variety of business contexts.
3. Integrate the knowledge and skills acquired to conduct research in an industry setting.
4. Deal with ambiguity and uncertainty,
5. Communicate the results of technical analysis to non-technical audiences.
6. Work effectively in teams.
The learning outcomes listed will be achieved by the acquisition and application of the following knowledge and skill outcomes:
Knowledge outcomes:
- Business functional areas
- a. Marketing
- b. Finance
- c. Accounting
- d. Economics
- e. Government Sector
- Data Warehousing
- Statistical literacy
Skill outcomes:
- Data analysis
-
- Exploring, summarizing, reporting
- Data visualization
- Statistical models and estimation methodology
- Machine learning algorithms
- Optimization techniques
-
- Supply Chain
- Price optimisation
- Sales force allocation and planning optimization
- Marketing mix modeling
- Decision Analysis
- Computing and Programming skills
- Communication and presentation skills
- Influencing skills
- Negotiation skills
Course structure
All subjects are compulsory. No electives. Subject levels: 9 for all subjects.
Compulsory subjects
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90499 | Introduction to Business Problems | March (On Campus - Parkville) |
12.5 |
BUSA90500 | Business Analytics Foundations | May (On Campus - Parkville) |
37.5 |
BUSA90501 | Advanced Business Analytics | August (On Campus - Parkville) |
37.5 |
BUSA90503 | Business Analytics Applications | Summer Term (On Campus - Parkville) |
37.5 |
Capstone subject
One of:
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90502 | Analytics Lab | October (On Campus - Parkville) |
25 |
BUSA90504 | Individual Research Project | August (On Campus - Parkville) |
25 |
Last updated: 12 November 2022