Master of Data Science
La Trobe University
Key Information
Campus location
Melbourne, Australia
Languages
English
Study format
On-Campus
Duration
2 years
Pace
Full time, Part time
Tuition fees
AUD 37,800 / per year *
Application deadline
Request info
Earliest start date
Request info
* additional fees may apply
Scholarships
Explore scholarship opportunities to help fund your studies
Introduction
Boost your career in the dynamic field of data science.
Organisations in every industry are asking big questions. With a Master of Data Science under your belt, you’ll have the skills to help answer them.
Data science professionals are in high demand in today's data-driven world. Whether you're already working in data science, or you're ready to make a career change, our Master of Data Science prepares you for a successful career in this exciting field.
Designed in collaboration with our industry partners, this degree gives you the knowledge, skills and hands-on experience to transition from university to the workplace. And with two early exit points along the way, you can be sure that every subject is contributing to your career.
You'll build fundamental skills in programming, databases, probability, statistics, data exploration and analysis. Got a particular interest in artificial intelligence, bioinformatics or sport analytics? This degree allows you to specialise in these areas and others, such as big data and cloud computing, business applications and data modelling and analytics.
As you study, you'll have opportunities to work with our industry partners on real-world projects and take on an industry work placement. If your sights are set on a research career, you can choose to undertake a thesis in computer science or statistics.
Every step of the way, our supportive and highly qualified teaching staff will be there to offer ongoing support and advice.
Key features
- Get hands-on industry experience at organisations such as Telstra, the Australian Institute of Sport and the Peter MacCallum Cancer Centre.
- Tailor your studies to your personal interests and professional goals. You'll have options to specialise in areas such as artificial intelligence, big data and cloud computing, bioinformatics, data modelling and analytics, or sports analytics.
- With two early exit points – the Graduate Certificate in Data Science Fundamentals and the Graduate Diploma in Data Science – every stage of this degree prepares you for future success.
- Our industry connection with Microsoft gives you access to free certifications in Microsoft Azure, Microsoft 365 and the Microsoft Office suite. These certifications – which you'll gain via on-campus exams – are applicable across a range of industries.
Program Outcome
You'll learn:
- Data science
Get practical experience with open-source software and platforms, including Python, R and Hadoop.
Understand database fundamentals, programming languages such as Java and Python, and cloud-based services offered by Amazon, Google, IBM and Microsoft. - Mathematics and statistics
Learn how to create complex models and use powerful tools for advanced analysis and problem-solving.
Build your skills using real data sets from our industry partners and learn how to solve data challenges facing businesses and organisations. - Project management
Learn how to manage large-scale IT projects and work in a team to develop a small-scale, industry-based system. - Complementary skills in other disciplines
Boost your knowledge through electives in business, health sciences, artificial intelligence and cybersecurity.
The qualification awarded on graduation is recognised in the Australian Qualifications Framework (AQF) as Level 9 - Masters Degree.
Career Opportunities
After graduation, you could work across a range of industries, including business and finance, science, education, health, and sports.
- Data scientist
Understand complex data and leverage it to the advantage of businesses and organisations. - Business analyst
Understand how businesses run and use data to solve problems and improve processes. - Health analyst
Gather, analyse and verify healthcare information. - Bioinformatician
Develop methods of research and analysis for understanding and leveraging biological and genomic data. - Machine learning engineer
Use your detailed understanding of machine learning, big data, cloud technology and mathematics to create effective machine-learning solutions.
The average salary for data scientists in Australia is A$130 000.*
*Seek, 2021 Data Scientist
Curriculum
Please note, the following course structure is indicative and subject to change depending on your course location, offer year or how you tailor your course with specialisations, majors, minors and electives. Structures for the following year are not normally finalised until October, so the sample provided is based on the most recently approved structure.
To qualify for the award of Master of Data Science, students must complete a total of 240 credit points across 2 years.
Year 1
Year 1 requires the completion of 120 credit points
including:
- 75 credit points from chosen Core
- 30 credit points from chosen Specialisation
- 15 credit points from chosen Electives
Year 2
Year 2 requires the completion of 120 credit points
including:
- 30 credit points from chosen Core
- 30 credit points from chosen Specialisation
- 60 credit points from chosen Core choice - Pathway
Core choice
Core choice subjects are one or more subject groups you need to select in your course. Core choice subjects may be specific to your course, major, minor, specialisation or other learning requirements.
Students to select one learning pathway from the list below.
Pathway
- Statistics thesis
- Computer science thesis
- Industry-based learning 1
- Industry-based learning 2
- Industry-based learning 3
Specialisations (StudyFlex available)
A specialisation is a sequence of related subjects studied in your course. In some courses, you need to complete at least one specialisation to attain your degree.
Students to select one specialisation
- Artificial intelligence analytics StudyFlex
- Big data and cloud computing StudyFlex
- Bioinformatics StudyFlex
- Business applications StudyFlex
- Data modelling and analytics StudyFlex
- Mathematical data science
- Sport analytics