Master of Analytics Management (MC-ANAMGT)

Masters (Coursework)Year: 2025 Delivered: On Campus (Parkville)

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Overview

Award titleMaster of Analytics Management
Year & campus2025 — Parkville
CRICOS code0100137
Fees informationSubject EFTSL, level, discipline and census date
Study level & typeGraduate Coursework
AQF level 9
Credit points150 credit points
Duration18 months full-time

The goal of this course is to equip its graduates with the capabilities to use their analytics skills to address business issues. The course is designed to develop an analytics generalist. The course will cover foundational general management subjects, analytics subjects as well as frameworks for applying the techniques to a variety of business contexts.

Entry requirements

  1. To be considered for entry, applicants must have completed:
  • An undergraduate degree; and
  • Minimum two years of documented full-time relevant work experience; and
  • A personal statement outlining why they wish to be considered for the program; and
  • Referees' reports

Meeting these requirements does not guarantee selection.


  1. In ranking applications, the Selection Committee will consider:
  • Prior academic performance; and
  • The work experience; and
  • The personal statement; and
  • The referees' reports


  1. 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. 


  1. 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.

Note.

Students who do not meet the progression requirements or choose not to complete the Master of Analytics Management, may exit the Master of Analytics Management with one of the following awards:

  • Professional Certificate in Business Administration: requires successful completion of two Category 1 subjects;
  • Professional Certificate in Analytics Management: requires successful completion of two Category 2 or Category 3 subjects;
  • Graduate Certificate in Business Administration: requires successful completion of four Category 1 subjects; or
  • Graduate Diploma in Analytics Management: requires successful completion of four subjects (must include Data Analysis) in Category 1 and any three subjects in Category 2, and one subject in Category 3

Information on the requirements that must be met for exit award are available in the Handbook.

Inherent requirements (core participation requirements)

Melbourne Business School welcomes applications from eligible students for a variety of graduate degrees offered by its programme portfolio. These degrees require following attributes for academic study:

  • The ability to explain and evaluate concepts, theories, and business operations of organisations
  • Ability to use analytic techniques to solve business problems

Melbourne Business School welcomes applications from students with disabilities and takes reasonable steps to implement adjustments to provide equal participation opportunities for students with disability.

Professional accreditation

AACSB

Intended learning outcomes

Students who complete this course will be able to:

Analyse data and build mathematical models to solve business problems:

  • Undertake statistical modelling of data
  • Build optimisation models
  • State a business problem clearly and choose an appropriate quantitative model for the situation

Translate between analytical models and the business outcomes of an organisation:

  • Identify issues and solutions within firms
  • Explain and critically analyse factors that influence decision making
  • Communicate effectively with both analytical professionals and top-level decision makers

Be an effective decision maker:

  • Apply ethical principles to address real-world issues and problems
  • Use evidence-based techniques to support decisions

Generic skills

  • High level of development: problem solving; statistical reasoning; application of theory to practice; interpretation and analysis; synthesis of data and other information; evaluation of data and other information; use of computer software; accessing data and other information from a range of sources.
  • Moderate level of development: written communication; critical thinking; receptiveness to alternative ideas.
  • Some level of development: collaborative learning; team work.

Graduate attributes

On successful completion of this degree graduates will be:

  • Adept at analysis and evaluation of business problems to enable evidence-based business and decision making;
  • Able to analyse data from both a business and analytics perspective;
  • Effective problem solvers as project leaders, analysts and managers in business context;
  • Proficient in professional knowledge and skills in business analytics;
  • Competent at analysing and evaluating information to enable evidence-based business decision making;
  • Strategic and critical thinkers in relation to business issues in organisations and markets;
  • Problem solvers in business systems through the application of appropriate theories, principles and data;
  • Effective communicators of business analytics concepts and solutions to peers and the wider community; and
  • Able to conduct basic research and to retrieve business and information technology information from a variety of sources.

Course structure

Students are required to achieve a grade of 70% minimum in Data Analysis to progress to Category 2 and Category 3 subjects and students cannot continue in the Master of Analytics Management course without meeting all the requirements below.

  1. Achieved a weighted average mark of at least H2B (70%) in a minimum of 6 subjects; and
  2. Had no more than one grade below 65 in the 6 subjects; and
  3. Had no fails in any of the 6 subjects

For students who do not meet the above requirements, they may exit the Master of Analytics Management course with an exit award if applicable.

Category 1: Foundation Management subjects

Code Name Study period Credit Points
BUSA90060 Data Analysis
January (On Campus - Parkville)
April (On Campus - Parkville)
June (On Campus - Parkville)
September (On Campus - Parkville)
 12.5

Plus any three of the following five subjects:

Code Name Study period Credit Points
BUSA90243 Marketing
January (On Campus - Parkville)
April (On Campus - Parkville)
June (On Campus - Parkville)
September (On Campus - Parkville)
 12.5
BUSA90227 Operations
January (On Campus - Parkville)
April (On Campus - Parkville)
April (On Campus - Parkville)
June (On Campus - Parkville)
September (On Campus - Parkville)
 12.5
BUSA90093 Finance
January (On Campus - Parkville)
April (On Campus - Parkville)
June (On Campus - Parkville)
September (On Campus - Parkville)
 12.5
BUSA90001 Financial Accounting
January (On Campus - Parkville)
April (On Campus - Parkville)
June (On Campus - Parkville)
September (On Campus - Parkville)
 12.5
BUSA90193 Managerial Economics
January (On Campus - Parkville)
April (On Campus - Parkville)
June (On Campus - Parkville)
September (On Campus - Parkville)
 12.5

Category 2: Analytics Foundations subjects

Code Name Study period Credit Points
BUSA90493 Business Analytics
June (On Campus - Parkville)
 12.5
BISY90016 Predictive Analytics
September (On Campus - Parkville)
 12.5
BISY90017 Quant. Decision Making & Optimisation
September (On Campus - Parkville)
 12.5
MGMT90244 Leading Data and AI Transformation
January (On Campus - Parkville)
 12.5

Category 3: Analytics Specialised subjects

Any two of the following three subjects:

Code Name Study period Credit Points
BUSA90521 Supply Chain Analytics Not available in 2025 12.5
FNCE90079 Finance and Accounting Analytics Not available in 2025 12.5
MKTG90039 Marketing Analytics
January (On Campus - Parkville)
 12.5

Category 4: Applied Analytics Lab Capstone

Code Name Study period Credit Points
BUSA90522 Applied Analytics Lab
January (On Campus - Parkville)
April (On Campus - Parkville)
 25

Last updated: 27 February 2025