Duration
2 years full time / 4 years part time
Mode (Location)
On campus (Parkville)
Intake
March
Key dates
Key dates
Fees
Commonwealth Supported Places (CSPs) available
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Entry schemes
Access Melbourne is available
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Course overview
Overview
Study data science
Develop in-demand data science skills
Join the rapidly evolving field of data analytics and build your advanced statistics, machine learning, and programming skills. Build foundational technical and analytical skills for working with large, complex collections of data. And dive deeper with specialisation streams and a dedicated major data science project.
Key features
- Build industry connections. Build connections with researchers from on-campus partners like the Australian Mathematical Sciences Institute and Melbourne Integrative Genomics.
- Flexible study options. Choose from four data science specialisations: foundational, statistical, computational, and computational and statistical.
- Showcase your skills. Apply data science tools to a practical problem in the final year capstone subject. Work individually or in a group and present your technically correct results in a client-ready format.
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Why study data science at Melbourne?
Combine a strong theoretical foundation with practical skills, and tailor your learning to suit your career goals. You will graduate with detailed technical understanding of advanced data science tools, including expertise in machine learning methods, advanced data mining, database systems, and computational statistics.
- Flexible entry. Enter with a computer science or statistics background, or complete core subject prerequisites if you’re coming from a different background.
- Solve real-world challenges. Apply your knowledge using public and private data sources.
- Go beyond technical skills. Choose an elective like science communication, or build job-ready skills with a science or technology internship.
Student support
The School of Mathematics and Statistics offers Master of Data Science students dedicated support from experienced academic advisors and peers.
- Research seminars. Learn from leading academics from the University research institutions, as well as partner organisations.
- Data Science Peer-to-Peer Mentoring. Connect with current students and build personal and supportive networks across the data science program. After your first year, take the opportunity to become a mentor yourself.
- Mathematics and Statistics Society. Engage with like-minded students through mathematically inspired events, study groups and seminars.
- Statistics and Mathematics Postgraduate Society. Designed specifically for postgraduate students, StAMPS offers academic and social support through events, study sessions, and seminars.
Stop 1 offers support across the full range of student services. Attend a workshop, visit in-person (on Swanston Street), or submit an enquiry online.
- Course planning and academic skills advice. Meet with an advisor or attend a workshop to make the most of your studies.
- Mentoring opportunities. Learn more about academic and peer mentoring opportunities.
- Global exchange and overseas study support. Explore overseas study opportunities with a wide range of global partners.
- Fees and scholarship information. Get on top of your finances and learn about scholarships.
- Visa information. Have your visa questions answered.
- Wellbeing and accommodation. Understand options for financial support, accommodation, and counselling.
- Student administration. Help with all aspects of student admin, including organising your student cards and IT.
What students say
Meet Mayra Bornacelly, a Master of Data Science student. Mayra shares how the degree has prepared her for a role in industry.
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Learn more about the School of Mathematics and Statistics.