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2 Years On Campus Masters Program
University of MelbourneThe Master of Data Science with a Specialisation in Mathematics at the University of Melbourne is designed for those who are passionate about harnessing the power of data to solve complex problems. This program is ideal for students with a strong mathematical background who wish to deepen their analytical skills and apply them in various industries, from finance to healthcare.
Curriculum Structure:
Year 1: Foundation subjects in statistics, mathematics, computer programming, data management and computational thinking, followed by core Data Science subjects covering statistical modelling, machine learning and data analysis.
Year 2: Advanced Data Science study with a mathematics/statistics-focused specialisation, including advanced statistical or mathematical techniques, computational methods and data analysis, followed by a capstone project applying data science to a practical real-world problem.
Focus Areas: Data analysis, machine learning, statistical modeling, big data technologies.
Learning Outcomes: Proficiency in data manipulation, advanced statistical analysis, algorithm development, and effective communication of data-driven insights.
Professional Alignment (Accreditation): The program is aligned with industry standards and is recognized by relevant professional bodies, ensuring that graduates are well-prepared for the job market.
Reputation (Employability Rankings): The University of Melbourne consistently ranks among the top universities globally, with high employability rankings in QS and The Guardian, reflecting the strong demand for its graduates in the data science field.
At the University of Melbourne, the Master of Data Science with a specialization in Mathematics offers students a unique opportunity to gain practical skills that are essential in today’s data-driven world. The program emphasizes experiential learning, allowing students to engage in real-world projects, collaborate with peers, and utilize cutting-edge tools and facilities. This hands-on approach not only enhances your understanding of theoretical concepts but also prepares you for a successful career in data science.
Here are some key aspects of the experiential learning opportunities available in this program:
- Group Projects: Collaborate with fellow students on team-based projects that simulate real-world data challenges, fostering teamwork and communication skills.
- Internships: Gain valuable industry experience through internship opportunities that connect you with leading organizations in the field of data science.
- Software and Tools: Access to industry-standard software such as Python, R, and SQL, as well as data visualization tools like Tableau and Power BI, ensuring you are well-versed in the technologies used in the field.
- Research Laboratories: Utilize state-of-the-art research facilities, including the Melbourne Data Analytics Platform, which provides access to advanced computational resources and data sets.
- Field Trips: Participate in excursions to local tech companies and data science conferences, offering insights into industry practices and networking opportunities.
- Libraries and Resources: Benefit from extensive library resources, including access to specialized databases and journals that support your research and learning.
- Collaboration with Institutes: Engage with renowned institutes such as the Melbourne School of Engineering and the Melbourne Institute of Applied Economic and Social Research, enhancing your academic experience through interdisciplinary collaboration.
The Master of Data Science with a specialization in Mathematics at the University of Melbourne equips graduates with the skills and knowledge to excel in a rapidly growing field. Graduates can look forward to exciting career opportunities in roles such as Data Scientist, Data Analyst, Machine Learning Engineer, and Quantitative Analyst. The demand for data professionals is soaring, making this program a strategic choice for your future:
- University Services: The University of Melbourne offers dedicated career services, including personalized career coaching, resume workshops, and networking events with industry leaders to help you secure your dream job.
- Employment Stats and Salary Figures: According to recent data, over 90% of graduates from the Master of Data Science program find employment within six months of graduation, with starting salaries averaging around AUD 85,000 per year.
- University–Industry Partnerships: The university has strong partnerships with leading companies such as IBM, Deloitte, and ANZ, providing students with opportunities for internships, collaborative projects, and real-world experience.
- Long-term Accreditation Value: The program is accredited by the Australian Computer Society, ensuring that your qualification is recognized and respected in the industry.
- Graduation Outcomes: Graduates are well-prepared to tackle complex data challenges and are highly sought after by employers across various sectors, including finance, healthcare, and technology.
Further Academic Progression: After completing the Master of Data Science, you may choose to pursue a PhD in Data Science or a related field, allowing you to delve deeper into research and contribute to advancements in data methodologies. This path can open doors to academic positions, research roles, or specialized industry positions that require advanced expertise.
Have completed a bachelor degree (AQF7) in any discipline with a weighted average mark (WAM) of 65%, or equivalent.
Applicants must have completed a 12.5-point computer programming subject, MAST10006 Calculus 2 (or equivalent), and MAST10007 Linear Algebra (or equivalent).
You can use our graduate coursework grade conversion eligibility calculator to get an indication of whether you are eligible for this course based on your previous studies and Weighted Average Mark (WAM).
IELTS: Overall score of 6.5, with a minimum score of 6.0 in Writing, Speaking, Reading, and Listening.
TOEFL: Overall score of 81, with a minimum score of 19 in Writing and Speaking, and 16 in Reading and Listening.
CSPs are university places subsidised by the Australian Government. Generally, Commonwealth supported students are still required to pay a discipline-based Student contribution amount(9,537).
Campus location: Parkville campus, Melbourne, Victoria, Australia. USA: Bachelor’s degree equivalent to AQF Level 7 in any discipline with a WAM of 65% or equivalent.India: Bachelor’s degree equivalent to AQF Level 7 in any discipline with a WAM of 65% or equivalent.UK: Bachelor’s degree equivalent to AQF Level 7 in any discipline with a WAM of 65% or equivalent.China: Bachelor’s degree equivalent to AQF Level 7 in any discipline with a WAM of 65% or equivalent.Data ScientistData AnalystStatisticianMachine Learning EngineerQuantitative AnalystData EngineerBusiness Intelligence AnalystStatistical ConsultantResearch ScientistData Science Consultant
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