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Graduate Certificate in Business Analytics (GC-BUSANA)
Graduate CertificateYear: 2023 Delivered: On Campus (Parkville)
About this course
Director
Simon Holcombe
Overview
Award title | Graduate Certificate in Business Analytics |
---|---|
Year & campus | 2023 — Parkville |
Fees information | Subject EFTSL, level, discipline and census date |
Study level & type | Graduate Coursework |
AQF level | 8 |
Credit points | 50 credit points |
Duration | 12 months part-time |
The goal of this course is to equip its graduates with specialised data analytic techniques. The course has eight specialised disciplinary streams for students to choose from. Each stream covers foundation and advanced data analytics in its specialised disciplinary area, as well as frameworks for applying those techniques to its 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
- two years of professional working experiences
Meeting these requirements does not guarantee selection.
2. In ranking applications, the Selection Committee will consider:
- prior academic performance; and
- professional working experiences; and
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)
Inherent requirements are the abilities, knowledge and skills needed to complete this course that must be met by all students. For information on the inherent requirements specific to this course contact the course/program coordinator. In some circumstances reasonable adjustments may be available to enable students to meet these requirements while still preserving the academic integrity of the university's learning, assessment and accreditation processes. For more information on how to seek these adjustments refer to the Student Equity and Disability Support website: https://services.unimelb.edu.au/student-equity/home
Intended learning outcomes
On completion of this course, graduates 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
Generic skills
- Communication and presentation skills
- Negotiation skills
- Influencing skills
- Working in teams
Graduate attributes
- Discipline knowledge and skills
- Business analytical skills
- Teamwork and communication skills
- Creative and critical thinking
- Problem solving skills
Course structure
The Graduate Certificate in Business Administration consists of 50 credit points in total.
Stream A (1)
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90537 | Coding for Business Problems |
March (On Campus - Parkville)
July (On Campus - Parkville)
|
12.5 |
BUSA90539 | Business Data Platforms |
March (On Campus - Parkville)
September (On Campus - Parkville)
|
12.5 |
BUSA90538 | Decision Making and Optimisation |
March (On Campus - Parkville)
July (On Campus - Parkville)
|
12.5 |
BUSA90536 | Statistical Learning for Business |
March (On Campus - Parkville)
July (On Campus - Parkville)
|
12.5 |
Stream B (2)
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90537 | Coding for Business Problems |
March (On Campus - Parkville)
July (On Campus - Parkville)
|
12.5 |
BUSA90536 | Statistical Learning for Business |
March (On Campus - Parkville)
July (On Campus - Parkville)
|
12.5 |
BUSA90542 | Machine Learning & AI for Business | May (On Campus - Parkville) |
12.5 |
BUSA90543 | Text Analytics for Business |
May (On Campus - Parkville)
September (On Campus - Parkville)
|
12.5 |
Stream C (3 & 4)
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90539 | Business Data Platforms |
March (On Campus - Parkville)
September (On Campus - Parkville)
|
12.5 |
BUSA90536 | Statistical Learning for Business |
March (On Campus - Parkville)
July (On Campus - Parkville)
|
12.5 |
BUSA90541 | Predictive Business Analytics |
May (On Campus - Parkville)
September (On Campus - Parkville)
|
12.5 |
and one of
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90546 | Risk Analytics | October (On Campus - Parkville) |
12.5 |
BUSA90540 | Causal Analytics for Business | May (On Campus - Parkville) |
12.5 |
Stream D (5 & 6)
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90536 | Statistical Learning for Business |
March (On Campus - Parkville)
July (On Campus - Parkville)
|
12.5 |
BUSA90541 | Predictive Business Analytics |
May (On Campus - Parkville)
September (On Campus - Parkville)
|
12.5 |
BUSA90540 | Causal Analytics for Business | May (On Campus - Parkville) |
12.5 |
and one of
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90544 | Marketing Analytics | October (On Campus - Parkville) |
12.5 |
BUSA90546 | Risk Analytics | October (On Campus - Parkville) |
12.5 |
Stream E (7 & 8)
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90538 | Decision Making and Optimisation |
March (On Campus - Parkville)
July (On Campus - Parkville)
|
12.5 |
BUSA90536 | Statistical Learning for Business |
March (On Campus - Parkville)
July (On Campus - Parkville)
|
12.5 |
BUSA90545 | Supply Chain Analytics |
September (On Campus - Parkville)
October (On Campus - Parkville)
|
12.5 |
and one of
Code | Name | Study period | Credit Points |
---|---|---|---|
BUSA90541 | Predictive Business Analytics |
May (On Campus - Parkville)
September (On Campus - Parkville)
|
12.5 |
BUSA90540 | Causal Analytics for Business | May (On Campus - Parkville) |
12.5 |
Last updated: 30 January 2024