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I want more infoHighlights
- 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
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
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
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)
- Data Exploration and Mining (IFN509)
- 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)
- 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)
- Data Exploration and Mining (IFN509)
- 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)
- 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.
- Course code
- IN27
- CRICOS code
- 098601J
-
- Gardens Point
-
- Gardens Point
- 1 - 2 years full-time
- 2 - 4 years part-time
- 2 years full-time
- February and July
- February and July
2 year program
A recognised bachelor degree
(or higher qualification) in any discipline with a minimum grade point average (GPA) of 4.00 (on QUT's 7 point scale).
1.5 year program
A recognised bachelor degree (or higher
qualification) in information technology or mathematics with a minimum grade point average (GPA) score of 4.00 (on QUT's 7 point scale).
1 year program
- A recognised bachelor honours degree in information technology or mathematics with a minimum grade point average of 4.00 (on QUT’s 7 point scale)
- A recognised bachelor degree in information technology or mathematics with a minimum grade point average (GPA) score of 4.00 (on QUT's 7 point scale) plus completion with a minimum grade point average (GPA) score of 4.00 of one of QUT's:
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 |
|---|---|---|---|---|---|
|
Pearson PTE (Academic)
Test must be taken no more than 2 years prior to the QUT course commencement date. |
58 | 50 | 50 | 50 | 50 |
|
Cambridge English Score
Test must be taken no more than 2 years prior to the QUT course commencement. 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 no more than 2 years prior to the QUT course commencement date. |
6.5 | 6 | 6 | 6 | 6 |
|
TOEFL iBT
Test must be taken no more than 2 years prior to the QUT course commencement date. |
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
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: $24,700 per year full-time (96 credit points)
2021 fees
2021: $34,100 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.
You can apply for scholarships to help you with study and living costs.