Master of Data Science 24 months Postgraduate Programme By La Trobe University |TopUniversities
Programme Duration

24 monthsProgramme duration

Tuitionfee

43,800 AUDTuition Fee/year

Main Subject Area

Data Science and Artificial IntelligenceMain Subject Area

Programme overview

Main Subject

Data Science and Artificial Intelligence

Degree

Other

Study Level

Masters

Study Mode

Blended

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.



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.

Programme overview

Main Subject

Data Science and Artificial Intelligence

Degree

Other

Study Level

Masters

Study Mode

Blended

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.



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.

Admission Requirements

176+
58+
79+
6.5+
Prerequisites

To be considered for admission to this degree you will need to meet at least one of the following criteria:

completion of an Australian bachelor degree or equivalent in any discipline.
OR

completion of the Postgraduate Qualifying Program (PPN001)

2 Years
Mar
Jul

Tuition fees

Domestic
34,800 AUD
International
43,800 AUD

Scholarships

Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.

To help students navigate this challenging process, we recommend the following articles:

More programmes from the university

Postgrad Programmes 333