Monash University
Master of Analytics
- Delivery: Online
- Study Level: Postgraduate
- Duration: 24 months
- Course Type: Master's
Develop a comprehensive analytical toolkit with the technical know-how to shape modern business decision-making.
Course overview
With this online master’s degree, you will extend your expertise in analytics and gain critical knowledge and skills required to make informed business decisions using complex data.
You will gain foundational knowledge in Python programming and data modelling while completing specialist units in accounting analytics, data visualisation, and data science. As part of your degree, you will also have the opportunity to undertake online elective units to broaden your professional development or specialise further across various areas.
This course is ideal if you want to gain specialised knowledge in analytics or formalise your work experience with a degree from a leading global university. As a graduate, you will have the knowledge and skills to work across multiple sectors and industries. This degree will ensure you’re ready to work in a rapidly changing business environment.
Key facts
What you will study
To complete the Master of Analytics, you must complete 12 units (72 credit points). It consists of Part A. Mastery Knowledge, eight units (48 credit points) and Part B. Electives four units (24 credit points).
Part A. Analytics specialisation studies
Complete the following units:
- Introduction to Accounting Analytics (six credit points)
- Predictive Analytics in Business (six credit points)
- Introduction to Data Analysis (six credit points)
- Collaborative and Reproducible Practices (six credit points)
- Data visualisation and Analytics (six credit points)
- Introduction to Python (six credit points)
- Statistical Data Modelling (six credit points)
- Mathematical Foundations for Data Science and AI (six credit points)
Part B. Application studies
You must complete four units (24 credit points) from Monash Online programs at Level 4 or 5*.
*At least one Part B Application studies unit must be at Level 5.
- Introduction to accounting analytics (six credit points)
- Predictive analytics in business (six credit points)
Entry requirements
Entry level 1: 72 credit points to complete
Duration: Two years part-time
Applicants must have one of the following:
- An Australian bachelor’s degree in a relevant discipline* or an equivalent qualification with at least a credit (60%) average or equivalent Grade Point Average (GPA).
- An Australian bachelor’s degree or equivalent qualification with at least a credit (60%) average or equivalent Grade Point Average, plus at least two years of relevant work experience**.
Entry level 2: 48 credit points to complete
Duration: 1.4 years part-time
- Applicants require a Monash University Graduate Certificate of Analytics with at least a credit (60%) average.
*Relevant disciplines include analytics, business statistics, econometrics, mathematics and business.
**Applicants applying based on work experience are required to provide a detailed curriculum vitae outlining their employment history and professional experience.
For entry into level 1 or 2, applicants must supply a short candidate statement demonstrating professional interest and existing quantitative analysis skills and have successfully completed a first-year undergraduate statistics unit or provide evidence of qualifications/training or experience that the faculty considers to be equivalent.
English language requirements
For entry to Monash University, you must meet the minimum English language requirements. You can do this by completing one of the qualifications listed on their website.
If you've completed several measures of English proficiency over a period of time, the highest valid measure will be accepted as long as it's been taken within the required time limitations.
University entrance requirements
Minimum entrance requirements apply for admission to Monash University Australia.
Recognition of Prior Learning
You may be able to get credit for your course based on prior formal, non-formal or informal learning. To apply, you will need to provide supporting documentation outlined by the university. Contact the university for more information.
Outcomes
Career outcomes
In a world where data is king, Data Analysts are some of the most sought-after, emerging professionals.
Learning outcomes
- Data analysis: Convert raw data into actionable insights.
- Predictive analytics: Discover the story behind the data to inform evidence-based and strategic decision making.
- Python and R programming: Acquire skills in the industry-standard Python programming and R programming languages to conduct rigorous data modelling and visualisation.
Fees and FEE-HELP
Average 2025 total course fee: $37,100 (domestic full-fee paying place)
All costs are calculated using current rates and are based on a study load of 24 credit points (normally four units) per semester or 48 credit points (normally eight units) per year.
A student’s annual fee may vary in accordance with:
- The number of units studied per term.
- The choice of major or specialisation.
- Choice of units.
- Credit from previous study or work experience.
- Eligibility for government-funded loans.
Student fees shown are subject to change. Contact the university directly to confirm.
FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university course.