• Foundations of Data Analytics

  In today’s data-driven world, a strong understanding of mathematics, probability and statistics is essential for making informed business decisions.
  
  This subject introduces you to these foundational concepts, blending theory with practical exercises to build confidence and prepare you for advanced analytics topics. 

• Analytics for Business Decisions

  Smart business decisions don’t come easy. But they’re what separate thriving businesses from the rest.
  
  This subject equips you with tools to navigate complex business environments, overcome cognitive biases and make better decisions through structured models and evidence-based approaches. 

• Data Visualisation for Analytics

  Data visualisation transforms complex datasets into powerful and compelling stories.
  
  In this subject, you will master the art and science of visual storytelling by using industry-standard tools to communicate insights effectively. 

• AI and Ethics in Analytics

  Artificial Intelligence (AI) is reshaping business analytics, but its use comes with ethical responsibilities.
  
  This subject reviews key AI concepts (such as machine learning, neural networks and predictive analytics) alongside key ethical frameworks, preparing you to implement AI responsibly in business contexts. 

• Data Platforms for Analytics

  In a tech-driven world, effective decision-making is shaped by reliable data.
  
  This subject teaches you how to design and implement data warehouses that power business insights, with a focus on cloud computing, data curation and CRM-oriented systems. 

• Programming for Analytics

  In this subject you will discover the essentials of programming. Using an intuitive high-level language, you’ll learn about variables, conditionals, functions, loops and how to design simple algorithms.
  
  Topics will be brought to life through practical, real-world examples, helping you build confidence even if you’re completely new to programming. 

• Modelling and Predictive Analytics

  Statistical modelling and prediction are used across many areas, from marketing and finance to human resources.
  
  This subject gives you the foundational skills to make sense of complex data and use it to support smart business decisions.
  
  Through real-world case studies and industry examples, you’ll learn a range of techniques, such as traditional regression, time-series analysis, multivariate models and contemporary approaches that use historical data. 

• Advanced Business Analytics: Machine Learning

  With growth of data online, there’s an essential need for businesses to find patterns and make sense of new information quickly. Machine learning gives us tools to do this automatically, helping us understand processes better and even predict future outcomes.
  
  In this subject, you’ll get introduced to key techniques like neural networks, support-vector machines, clustering and ensemble methods such as bagging, boosting and random forests. You’ll also get hands-on experience applying and evaluating these tools in real-world business scenarios.

• Applied Marketing Analytics

  This subject gives you hands-on experience with marketing analytics, using technology and data to make smarter business decisions.
  
  Through real-world case studies and practical exercises, you’ll develop the skills to analyse customer and market data, solve complex marketing challenges and influence key outcomes like customer satisfaction, brand loyalty and word-of-mouth referrals.

• Applied Investment Analytics

  Effective risk management is critical for organisational resilience.
  
  This subject equips you with the skills to analyse and mitigate risks using data analytics, bridging theory with practical application.
  
  Through case studies and hands-on exercises, you will explore topics like market risk modelling, portfolio management and operational risk evaluation.

  • ​​​​​​​Utilise data analytics techniques to measure and manage risk in financial and organisational settings 

  • Recognise the inherent challenges and uncertainties in risk management

  • Demonstrate proficiency in the technical aspects of contemporary risk analytics

• Applied Supply Chain Analytics

  Get ready to turn supply chain challenges into smart solutions.
  
  This subject gives you practical experience in using mathematical modelling and analytics to optimise logistics and supply chain operations. You’ll learn how to analyse and make decisions at strategic, tactical, and operational levels by covering areas like inventory management, facility location, and logistics planning.

  • ​​​​​​​​​​​​​​Identify key supply chain management metrics

  • Develop mathematical models for supply chain challenges such as location, inventory and process optimisation

  • Apply both exact and heuristic approaches for solving supply chain problems, evaluating their efficiency and applicability.

• Finance

  This subject addresses the foundations of valuation and financial management. Concepts addressed are relevant for a variety of organisations, as well as for personal financial planning and
  investments

• Marketing

  To be successful, organisations need to recognise, create, grow and protect market-based assets that influence demand.
  
  This subject focuses on the challenges organisations face in managing demand and how to address those challenges with optimal demand-side strategies.

• Operations

  In fiercely competitive global and dynamic environments, organisations face increasing pressures to exceed stakeholder expectations across measures such as sustainability, social responsibility, cost, quality, flexibility and innovativeness.
  
  This subject addresses the analysis, design, management and continuous improvement of business processes. It covers core operations concepts essential for leveraging an organisation’s capabilities to achieve sustainable competitive advantage. 

  • ​​​​​​​​​​​​​​Analyse an organisation's processes and evaluate their alignment with the organisation's overall strategy and positioning in the marketplace

  • Perform process analysis to identify existing bottlenecks and ways to reduce their impact and improve process efficiency

  • Apply frameworks for managing inventory

  • Use queuing models to propose relevant solutions to contain the effects of process variability

  • Use robust statistical process control techniques to ensure that a given process is fit for purpose

  • Apply Six-Sigma and Lean (Toyota Production System) principles to improve process performance.

• Applied Business Analytics Project
  This subject gives you hands-on experience in solving real business problems with practical analytics solutions through a collaborative group project.
  
  You'll develop skills in three key areas:
  • Problem-solving & translating methods: Learn how to identify and evaluate possible analytics solutions for typical business problems and choose the approach that works best.
     
  • Communication: Practice presenting your ideas clearly, both in writing and verbally. You’ll learn to explain technical concepts in ways that any stakeholder can understand.
     
  • Implementation: Discover how to pick the right software or programming tools for a given business challenge and use them to deliver effective, actionable analytics solutions. 
     
• Marketing Analytics Project
  This subject gives you hands-on experience in solving real marketing business problems with practical analytics solutions through a collaborative team project.
   
  • ​​​​​​​Problem-solving & translating methods: Identify and evaluate possible analytics solutions for marketing challenges and choose the approach that works best.
  • Communication: Practice presenting your ideas clearly, both in writing and verbally. You’ll learn to explain technical concepts in ways that any stakeholder can understand.
     
  • Implementation: Discover how to pick the right software or programming tools for a given business challenge and use them to deliver effective, actionable analytics solutions for real marketing problems.
     
• Investment Analytics Project
  In this capstone subject, you’ll work in teams to build an investment portfolio using a variety of analytics algorithms commonly used in the finance industry. You’ll gain hands-on experience applying real-world tools to analyse financial data, identify market patterns and make informed investment decisions.
  
  You’ll explore algorithms such as:
   
  • Fundamental analysis: evaluate the underlying value of securities using financial and economic data
     
  • Technical analysis: Identify trends and patterns from market price and volume data that may indicate future price movements
     
  • Quantitative analysis: Use statistical models and machine learning to predict market movements
     
  • Arbitrage: use price discrepancies between different markets or securities to generate profits
     
  • Trend following: Generate trading signals based on historical price trends
     
  • Mean reversion: Identify securities likely to return to historical price ranges
     
  • High-frequency trading: Execute rapid trades to take advantage of small market discrepancies.
     
  • Sentiment analysis: Analyse news and social media to gauge investor and market sentiment
    ​​​​​​​
  • Portfolio optimisation: Use models to optimise allocation of portfolio assets based on risk and return objectives. 
    ​​​​​​​
• Supply Chain Analytics Project
  This subject gives you hands-on experience in modelling and implementing optimisation solutions through a collaborative team project.
   
  • Problem-solving & translating methods: Identify and evaluate possible analytics solutions for marketing challenges and choose the approach that works best.
     
  • Communication: Practice presenting your ideas clearly, both in writing and verbally. You’ll learn to explain technical concepts in ways that any stakeholder can understand.
    ​​​​​​​
  • Implementation: Discover how to pick the right software or programming tools for a given business challenge and use them to deliver effective, actionable analytics solutions.
     
    • Develop the skill to interpret real business problems in supply chain or revenue management with ambiguity into mathematical optimisation models
    • Evaluate the benefits and disadvantages of using different algorithms (such as Linear Programming, Integer Linear Programming, Dynamic Programming, Local Search and Meta-heuristics) to solve an optimisation problem
    • Learn to construct a technical report appropriate for a technical and non-technical audience
    • Produce original work in an appropriate format which demonstrates analytical, research and problem-solving skills
    • Put into practice communication, interpersonal, organisational and time management skills in a workplace context. 

To apply for the Melbourne Business School online Master of Applied Business Analytics​, you must have:  

• A university degree in any discipline and weighted average mark (WAM) of 65% in the Graduate Certificate in Applied Business Analytics, or 

• A university degree in one of the related areas: commerce, mathematics, physics, computer science, information systems, engineering or science and 

• Two years of documented full-time professional work experience 

• Meet the University’s English Language requirements.

Documented evidence of meeting the accepted minimum scores within the previous 24 months may be required.  

The minimum accepted scores are:  

• IELTS (Academic English only): Overall score of 7.0 (with no individual band less than 7.0)

• TOEFL Internet-based Test: Overall score of 91 (with writing 26; speaking 24; reading 22; listening 22) 

• Pearson Test of English Academic (PTE): Overall score of 72 (with writing 75; speaking 76; reading 72; listening 72)

• Cambridge C1 Advanced: Overall score of 178 (with writing 193; speaking 194; reading 179; listening 175)  

• LanguageCert Academic: Overall score of 73 (with writing 78; speaking 82; reading 71; listening 67) 

• Michigan English Test (MET): Overall score of 62 (with writing 74; speaking 59; reading 63; listening 61). 

For more information on English language requirements, visit the University of Melbourne website.  

$5,308 per subject*, a total of $63,696 for the program*.  

FEE-HELP is available for eligible Australian citizens.  

*Fees listed are for calendar year 2026. Melbourne Business School Online reserves the right to adjust course fees annually.