Master of Data Analytics

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.

Domestic Students

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.

International Students

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.

2 year program

1.5 year program

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: Graduate Certificate in Business Analysis Graduate Certificate in Computer Science Graduate Certificate in Cyber Security and Networks Graduate Certificate in Data Analytics

Careers and outcomes(DOM,INT)

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.

Early exit(DOM,INT)

Early exit option with the IN26 Graduate Certificate in Data Analytics upon completion of the required units.

Possible careers

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