Solve the challenges of the future

Learn from our experts and industry partners to develop leading data science skills.

Apply now

Choose Master of Data Science at La Trobe

Data scientists are in short supply but in demand by many industries. Rapid technological advances have created large volumes of complex data, and companies are seeking experts who can use this data to their advantage. Companies are competing fiercely for experts who can find ways to manage higher volumes of data and solve increasingly complex challenges.

La Trobe’s Master of Data Science is designed to give graduates a competitive edge through up-to-the-minute theoretical content, real-world practical experiences, and networking opportunities with industry leaders.

La Trobe ranks ‘above world standard’ for mathematical sciences and pure mathematics research and ‘well above world standard’ for statistics research in the 2015 ERA Australian Research Council rankings. You'll learn from academics who are at the forefront of the Big Data field. Students are taught the latest data science tools such as Apache Spark and Hadoop.

Select from one of three majors: bioinformatics, big data and cloud computing, or analytical science, and broaden your knowledge through a range of electives.  You'll graduate ready to tackle society’s next generation of challenges using your unique skills in big data computing, analytical modelling and intelligence systems.

Career opportunities

Data scientists work across sectors such as business, health, biology, logistics, information technology and more, to interpret big data and identify innovative opportunities.

La Trobe works in industry with hospitals, large internet companies and the Australian Institute of Sport to solve real-world data problems.

As a graduate you'll be well positioned for a career in a variety of roles including:

  • data scientist
  • business analyst
  • bioinformatician
  • quantitative specialist
  • supply chain analyst
  • data engineer.

This course allows you to work in any sector where data can help solve problems, this may be in fields such as:

  • health
  • science
  • information technology
  • marketing
  • finance
  • government

NOTE: Information on this page relates to 2017 courses and fees. 2018 course and fee information will be confirmed and published shortly. As this page is subject to change and updates, prospective students are advised to revisit this page on a regular basis to keep updated.

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Course details for local students

Master of Data Science

Course offer year:
2017
Semester starts:
Semester 1 and 2 (March and July)
Fees amount:
$27,250 per 120 credit points.
Campus:
Melbourne
Duration:
2 years full-time or part-time equivalent
Prerequisites:
Australian Bachelor degree (or equivalent) in computer science, information technology, computer engineering, or science with a major in mathematics or statistics. NB: Meeting minimum prerequisites does not guarantee an offer of a place. Entry into all La Trobe courses is based on competitive selection and there may be limited places available.
Additional information:
This course requires prior knowledge in cognate areas of either Computer Science, IT, and/or Mathematics and Statistics. The course starts with a semester of core fundamental subjects designed to address knowledge gaps in the required cognate skills. E.g. students who have completed a Computer Science degree will need to choose fundamental subjects in Statistics and vice versa.
See Student Handbook for more details:

The Handbook contains detailed course information designed for enrolled students, including course structures, electives and options. The delivery of this course can vary between campuses. For detailed information please select the relevant campus:

Sample course structure

Year 1

Semester 1

  • Academic Integrity Module (online)

Students must choose 4 of the following fundamental subjects depending on their background:

Computer Science students must undertake MAT/STA coded fundamental subjects. Mathematics and Statistics students must undertake CSE coded fundamental subjects.

Semester 1

  • Database Fundamentals
  • Number Systems and Linear Algebra

Semester 1 or 2

  • Object-Oriented Programming Fundamentals
  • Intermediate Object-Orientated Programming

Semester 2

  • Calculus and Differential Equations
  • Statistical Science
  • Probability Models

Year 2

Semester 1

  • Big Data Management on the Cloud
  • Computational Intelligence for Data Analytics
  • Students select a STA5 subject from the following list:

Semester 1

  • Analysis of Repeated Measures

Semester 2

  • Meta Analysis
  • Models for Bioinformatics

Semester 1 or 2

  • Industry Project in Data Science
  • Industry Placement
  • Industry Based Learning
  • Statistics Thesis
  • Computer Science Thesis

Semester 2

  • Data Exploration and Visualisation
  • Data Mining
  • Web Development on the Cloud

Students must complete CSE4, CSE5, MAT4, MAT5, STA4, STA5 or other approved elective subjects from the list below to the value of 45-60 credit points. If Thesis subjects undertaken 45 credit points of electives are required. If Industry Based Learning subjects undertaken 60 credit points of electives are required.

  • Decision Support Systems
  • Advanced Databases
  • Bioinformatics Technologies
  • Data Warehouse Concepts and Design
  • Algorithms and Data Structures (PG)
  • Epidemiology and Research Methods
  • Epidemiology and Demography
  • Methods in GIS
  • Health Data Analysis A
  • Predictive Analysis
  • Visual Analysis
  • Customer Analytics and Social Media
  • Advanced Time-Series Econometrics

This sample course structure is only indicative. For an up to date version please consult the Handbook.

Specialisations, majors and minors

Big data and cloud computing

Cloud computing is fast eliminating the need for other more expensive hardware solutions and the dedicated space and software they require. By specialising in cloud computing and big data you’ll be invaluable in helping organisations to understand this new technology and to interpret the high volumes of data it produces.

Due to the ever-evolving nature of cloud computing technology, the demand for specialists is set to rise as products and services expand.

You’ll be qualified to work at the forefront of this industry, acting on insights garnered from large data sets and planning strategically based on your scientific findings.

Analytical science

As the amount of data streaming into businesses and science grows, and the complexity of this data increases, it’s vital to find graduates skilled in data analytics. Employees who can understand patterns and trends in data and  use them to make predictions are highly sought after and recruitment spans across all kinds of industries.

Set yourself up as an expert in data interpretation. Learn about practical data analysis and develop a high level of proficiency in modern statistical software. Get hands-on by selecting a major that uses real-world data sets and real-life problems to solve.

This specialisation covers sub-disciplines such as meta-analysis, analysis of repeated measures data, models for bioinformatics, and various elective subjects in advance statistics, health sciences, business and computing technologies.

Bioinformatics

Bioinformatics relates to biological data. That is, the collection, classification, storage and analysis of biochemical and biological information using computers - as applied to molecular genetics and genomics. Harness your mathematics, statistics and data analytics skills in the field of health and biology to maximise your career potential.

Gain knowledge and practical experience in database management, use of algorithms and statistics, and the latest statistical tools used to identify, interpret and mine data sets.

Our bioinformatics major uses Big Data to solve real-world issues so you can apply your knowledge and skills in one of society’s most important industries.

Contact us

Considering postgraduate study?

Personalise your own course guide in three quick and easy steps.

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Solve the challenges of the future

Learn from our experts and industry partners to develop leading data science skills.

Enquire now

Choose Master of Data Science at La Trobe

Data scientists are in short supply but in demand by many industries. Rapid technological advances have created large volumes of complex data, and companies are seeking experts who can use this data to their advantage. Companies are competing fiercely for experts who can find ways to manage higher volumes of data and solve increasingly complex challenges.

La Trobe’s Master of Data Science is designed to give graduates a competitive edge through up-to-the-minute theoretical content, real-world practical experiences, and networking opportunities with industry leaders.

La Trobe ranks ‘above world standard’ for mathematical sciences and pure mathematics research and ‘well above world standard’ for statistics research in the 2015 ERA Australian Research Council rankings. You will learn from academics who are at the forefront of the Big Data field. Students are taught the latest data science tools such as Apache Spark and Hadoop.

Select from one of three majors: bioinformatics, big data and cloud computing, or analytical science, and broaden your knowledge through a range of electives.  You will graduate ready to tackle society’s next generation of challenges using your unique skills in big data computing, analytical modelling and intelligence systems.

Career opportunities

Data scientists work across sectors such as business, health, biology, logistics, information technology and more, to interpret big data and identify innovative opportunities.

La Trobe works in industry with hospitals, large internet companies and the Australian Institute of Sport to solve real-world data problems.

As a graduate you will be well positioned for a career in a variety of roles including:

  • data scientist
  • business analyst
  • bioinformatician
  • quantitative specialist
  • supply chain analyst
  • data engineer.

This course allows you to work in any sector where data can help solve problems, this may be in fields such as:

  • health
  • science
  • information technology
  • marketing
  • finance
  • government

NOTE: Information on this page relates to 2017 courses and fees. 2018 course and fee information will be confirmed and published shortly. As this page is subject to change and updates, prospective students are advised to revisit this page on a regular basis to keep updated.

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Course details for international students

Master of Data Science (092396B)

Course offer year:
2017
Semester starts:
Semester 1 and 2 (March and July)
Fees amount ($A):
31 000
Campus:
Melbourne
Duration:
2 years full-time
English language requirements:
UG and PG (including HDR) Option 1: Academic 6.5, no band less than 6.0
Academic entry requirements:
Students must have completed a degree equivalent to a degree from an Australian university in computer science, information technology, computer engineering, or science with a major in mathematics or statistics. NB: Meeting minimum entry requirements does not guarantee an offer of a place. Entry into all La Trobe courses is based on competitive selection and there may be limited places available.
See Student Handbook for more details:

The Handbook contains detailed course information designed for enrolled students, including course structures, electives and options. The delivery of this course can vary between campuses. For detailed information please select the relevant campus:

Sample course structure

Year 1

Semester 1

  • Academic Integrity Module (online)

Students must choose 4 of the following fundamental subjects depending on their background:

Computer Science students must undertake MAT/STA coded fundamental subjects. Mathematics and Statistics students must undertake CSE coded fundamental subjects.

Semester 1

  • Database Fundamentals
  • Number Systems and Linear Algebra

Semester 1 or 2

  • Object-Oriented Programming Fundamentals
  • Intermediate Object-Orientated Programming

Semester 2

  • Calculus and Differential Equations
  • Statistical Science
  • Probability Models

Year 2

Semester 1

  • Big Data Management on the Cloud
  • Computational Intelligence for Data Analytics
  • Students select a STA5 subject from the following list:

Semester 1

  • Analysis of Repeated Measures

Semester 2

  • Meta Analysis
  • Models for Bioinformatics

Semester 1 or 2

  • Industry Project in Data Science
  • Industry Placement
  • Industry Based Learning
  • Statistics Thesis
  • Computer Science Thesis

Semester 2

  • Data Exploration and Visualisation
  • Data Mining
  • Web Development on the Cloud

Students must complete CSE4, CSE5, MAT4, MAT5, STA4, STA5 or other approved elective subjects from the list below to the value of 45-60 credit points. If Thesis subjects undertaken 45 credit points of electives are required. If Industry Based Learning subjects undertaken 60 credit points of electives are required.

  • Decision Support Systems
  • Advanced Databases
  • Bioinformatics Technologies
  • Data Warehouse Concepts and Design
  • Algorithms and Data Structures (PG)
  • Epidemiology and Research Methods
  • Epidemiology and Demography
  • Methods in GIS
  • Health Data Analysis A
  • Predictive Analysis
  • Visual Analysis
  • Customer Analytics and Social Media
  • Advanced Time-Series Econometrics

This sample course structure is only indicative. For an up to date version please consult the Handbook.

Specialisations, majors and minors

Big data and cloud computing

Cloud computing is fast eliminating the need for other more expensive hardware solutions and the dedicated space and software they require. By specialising in cloud computing and big data you’ll be invaluable in helping organisations to understand this new technology and to interpret the high volumes of data it produces.

Due to the ever-evolving nature of cloud computing technology, the demand for specialists is set to rise as products and services expand.

You’ll be qualified to work at the forefront of this industry, acting on insights garnered from large data sets and planning strategically based on your scientific findings.

Analytical science

As the amount of data streaming into businesses and science grows, and the complexity of this data increases, it’s vital to find graduates skilled in data analytics. Employees who can understand patterns and trends in data and  use them to make predictions are highly sought after and recruitment spans across all kinds of industries.

Set yourself up as an expert in data interpretation. Learn about practical data analysis and develop a high level of proficiency in modern statistical software. Get hands-on by selecting a major that uses real-world data sets and real-life problems to solve.

This specialisation covers sub-disciplines such as meta-analysis, analysis of repeated measures data, models for bioinformatics, and various elective subjects in advance statistics, health sciences, business and computing technologies.

Bioinformatics

Bioinformatics relates to biological data. That is, the collection, classification, storage and analysis of biochemical and biological information using computers - as applied to molecular genetics and genomics. Harness your mathematics, statistics and data analytics skills in the field of health and biology to maximise your career potential.

Gain knowledge and practical experience in database management, use of algorithms and statistics, and the latest statistical tools used to identify, interpret and mine data sets.

Our bioinformatics major uses Big Data to solve real-world issues so you can apply your knowledge and skills in one of society’s most important industries.

Contact us