Highlights

  • Be at the cutting edge of a booming new field of expertise that can be applied across industries.
  • Translate data into insight and intelligence to be able to drive change and make key decisions.
  • Solve domain-relevant problems by synthesising knowledge from mathematics, statistics, computer science, information systems and business process management.
  • Learn from expert academics and leading researchers who apply data science and data analytics to a range of real-world challenges, and who have world-wide industry connections.

Highlights

  • Be at the cutting edge of a booming new field of expertise that can be applied across industries.
  • Translate data into insight and intelligence to be able to drive change and make key decisions.
  • Solve domain-relevant problems by synthesising knowledge from mathematics, statistics, computer science, information systems and business process management.
  • Learn from expert academics and leading researchers who apply data science and data analytics to a range of real-world challenges, and who have world-wide industry connections.

Why choose this course?

Be future-focused and stay ahead of the curve. Drive real change and impact key decisions by learning how to make sense of the volume, variety, and velocity of data we collect as a society.

Our academics are world leaders in research and have strong industry ties that ensures the relevance of teaching material and high-quality learning experiences for students.

Real-world learning

This course is designed to specifically meet industry needs. We’ve brought together expertise in statistics, computer science, and business process management disciplines to deliver real-world learning opportunities.

You'll:

  • build significant project-based experience that allows you to constructively apply your analytical skills to complex problem domains
  • experience applying high-order thinking strategies within data-rich contexts through the synthesis of multiple sources of information
  • apply specialist abstraction and synthesis techniques to solve complex data analytics problems that are inspired by real-world scenarios.

Explore this course

What to expect

This course will prepare you for a future-focused career in the fast-paced, ever-changing world of data analytics. With a collaborative curriculum across disciplines you’ll not only learn theories and methods, but you’ll apply that knowledge to predict, forecast, visualise and make decisions in a range of applied areas.

You will study specialist units in advanced statistical data analysis, data mining techniques and applications, data manipulation, analytics for information professionals and advanced stochastic modelling.

Careers and outcomes

Careers and outcomes

When you graduate, you’ll be able to apply different approaches, techniques and tools to data in different industry contexts to solve complex problems.

You'll have the skills necessary to transform data into knowledge for any industry, including banking and finance, media and communications, health, education, information technology, engineering, agriculture and mining.

Possible careers

  • Data Analyst
  • Data Analytics Specialist
  • Data Systems Developer
  • Data-Driven Decision Maker

Details and units

You must complete 192 credit points of course units, consisting of:

  • 48 credit points of core units
  • 48 credit points of professional preparation units 
  • 48 credit points of advanced units
  • 48 credit points of elective units selected from an approved list.

Selecting your units

When you finish this course, you will emerge with skills and a specialisation in one of:

  • data analysis
  • data systems development
  • data-driven decision making.

Data analysis

As a data analyst, you apply your data mining and modelling skills to perform analysis of data to inform evidence-based decision making. You will be experienced in understanding and using statistical methods in this process. You will use appropriate tools to create data visualisations that effectively communicate data-driven insights to broader audiences.

Suggested professional preparation and advanced units selection:

  • Databases (IFN554) + Introduction to Programming (IFN555)
  • Data Exploration and Mining (IFN509)
  • Biomedical Data Science (IFN646)
  • Text, Web and Media Analytics (IFN647)
  • Statistical Data Analysis (MXN500)
  • Stochastic Modelling (MXN501)
  • Advanced Statistical Data Analysis (MXN600)
  • Advanced Stochastic Modelling (MXN601).

Data systems development

As a data systems development professional, you will use highly technical skills to architect computationally efficient data analysis solutions to reveal insights that can't be achieved with existing methods and tools.

Suggested professional preparation and advanced units selection:

  • Systems Analysis and Design (IFN552) + Object Oriented Programming (IFN556)
  • Databases (IFN554) + Introduction to Programming (IFN555)
  • Data Exploration and Mining (IFN509)
  • Data Mining Technology and Applications (IFN645)
  • Biomedical Data Science (IFN646)
  • Advanced Information Storage and Retrieval (IFN647)
  • Statistical Data Analysis (MXN500)
  • Advanced Statistical Data Analysis (MXN600)

Data-driven decision-making

As a data-driven decision maker, you'll use insights provided by data analysts for forecasting future demand, risk assessment, and the development of business insights. Your broad knowledge of data science tools and techniques is employed to interpret results and design new solutions to drive business transformation.

Suggested professional preparation and advanced units selection:

  • Introduction to Programming (IFN555) + Object Oriented Programming (IFN556)
  • Fundamentals of Business Process Management (IFN515)
  • Data Mining Technology and Applications (IFN645)
  • Advanced Information Storage and Retrieval (IFN647)
  • Business Process Analytics (IFN650)
  • Statistical Data Analysis (MXN500)
  • Stochastic Modelling (MXN501)
  • Advanced Statistical Data Analysis (MXN600)

Students in the 1.5 year program

Please note: study plans are determined based on prior qualifications. The placement of the 48 credit point reduction across the study plan may vary between students. Clarification can be sought from the Course Coordinators once admitted.

You must complete 192 credit points of course units, consisting of:

  • 48 credit points of core units
  • 48 credit points of professional preparation units 
  • 48 credit points of advanced units
  • 48 credit points of elective units selected from an approved list.

Selecting your units

When you finish this course, you will emerge with skills and a specialisation in one of:

  • data analysis
  • data systems development
  • data-driven decision making.

Data analysis

As a data analyst, you apply your data mining and modelling skills to perform analysis of data to inform evidence-based decision making. You will be experienced in understanding and using statistical methods in this process. You will use appropriate tools to create data visualisations that effectively communicate data-driven insights to broader audiences.

Suggested professional preparation and advanced units selection:

  • Databases (IFN554) + Introduction to Programming (IFN555)
  • Data Exploration and Mining (IFN509)
  • Biomedical Data Science (IFN646)
  • Text, Web and Media Analytics (IFN647)
  • Statistical Data Analysis (MXN500)
  • Stochastic Modelling (MXN501)
  • Advanced Statistical Data Analysis (MXN600)
  • Advanced Stochastic Modelling (MXN601).

Data systems development

As a data systems development professional, you will use highly technical skills to architect computationally efficient data analysis solutions to reveal insights that can't be achieved with existing methods and tools.

Suggested professional preparation and advanced units selection:

  • Systems Analysis and Design (IFN552) + Object Oriented Programming (IFN556)
  • Databases (IFN554) + Introduction to Programming (IFN555)
  • Data Exploration and Mining (IFN509)
  • Data Mining Technology and Applications (IFN645)
  • Biomedical Data Science (IFN646)
  • Advanced Information Storage and Retrieval (IFN647)
  • Statistical Data Analysis (MXN500)
  • Advanced Statistical Data Analysis (MXN600)

Data-driven decision-making

As a data-driven decision maker, you'll use insights provided by data analysts for forecasting future demand, risk assessment, and the development of business insights. Your broad knowledge of data science tools and techniques is employed to interpret results and design new solutions to drive business transformation.

Suggested professional preparation and advanced units selection:

  • Introduction to Programming (IFN555) + Object Oriented Programming (IFN556)
  • Fundamentals of Business Process Management (IFN515)
  • Data Mining Technology and Applications (IFN645)
  • Advanced Information Storage and Retrieval (IFN647)
  • Business Process Analytics (IFN650)
  • Statistical Data Analysis (MXN500)
  • Stochastic Modelling (MXN501)
  • Advanced Statistical Data Analysis (MXN600)

Students in the 1.5 year program

Please note: study plans are determined based on prior qualifications. The placement of the 48 credit point reduction across the study plan may vary between students. Clarification can be sought from the Course Coordinators once admitted.

Requirements

Course code
IN27
CRICOS code
098601J
Campus
  • Gardens Point
Campus
  • Gardens Point
Duration
2 years full-time
4 years part-time
Duration
2 years full-time
Entry
February and July
Entry
February and July

Academic entry requirements

1.5 year program

You must have a completed recognised bachelor degree in information technology or mathematics (or related field), with a minimum grade point average of 4.00 (on QUT's 7 point scale).

2 year program

You must have a completed recognised bachelor degree in any discipline with a minimum grade point average of 4.0 (on QUT's 7 point scale).

Note:  You don't need to apply separately for the 1.5 year program. You'll be automatically assessed for eligibility as part of our admission process.

 

Minimum academic requirements

Academic entry requirements

1.5 year program

You must have a completed recognised bachelor degree in information technology or mathematics (or related field), with a minimum grade point average of 4.00 (on QUT's 7 point scale).

2 year program

You must have a completed recognised bachelor degree in any discipline with a minimum grade point average of 4.0 (on QUT's 7 point scale).

Note: As part of our admission process, we will automatically assess you for the 1.5-year program. If you want to be considered for the 2 year program only, indicate this on your application form.

Minimum English language requirements

Select the country where you completed your studies to see a guide on meeting QUT’s English language requirements.

Your scores and prior qualifications in English-speaking countries are considered. Approved English-speaking countries are Australia, Canada, England, Ireland, New Zealand, Scotland, South Africa, United States of America and Wales.

If your country or qualification is not listed, you can still apply for this course and we will assess your eligibility.

We accept English language proficiency scores from the following tests.

English Test Overall Listening Reading Writing Speaking
Cambridge English Score
Test must be taken within 2 years of commencement at QUT. You must provide your Candidate ID and Candidate Secret Number, these are printed on your Cambridge English Confirmation of Entry. 		176 169 169 169 169
IELTS Academic
Test must be taken within 2 years of commencement at QUT. 		6.5 6 6 6 6
Pearson PTE (Academic)
Test must be taken within 2 years of commencement at QUT. 		58 50 50 50 50
TOEFL iBT
Test must be taken within 2 years of commencement at QUT. 		79 16 16 21 18

Don't have the English language score you need? We can help!

We offer English language programs to improve your English and help you gain entry to this course.

When you apply for this course, we will recommend which English course you should enrol in.

Haven't completed an English language test? We can help!

If you have not completed an English language test, you can sit the IELTS test at our IELTS test centre

Fees

Your actual fees may vary depending on which units you choose. We review fees annually, and they may be subject to increases.

2021 fees

2021: $25,700 per year full-time (96 credit points)

2021 fees

2021: $35,600 per year full-time (96 credit points)

2020 fees

2020: $24,700 per year full-time (96 credit points)

2020 fees

2020: $34,700 per year full-time (96 credit points)

Student services and amenities fees

You may need to pay student services and amenities (SA) fees as part of your course costs.

Find out more about postgraduate course fees

FEE-HELP: loans to help you pay your course fees

You may not have to pay anything upfront if you're eligible for a FEE-HELP loan.

Find out more about government loans

Scholarships

You can apply for scholarships to help you with study and living costs.

Browse all scholarships

You may also be eligible for

Centrelink payments