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Master of Data Science

Cairns, Online
March, September
2 years full time
This course is delivered in four separate parts.
Attendance mode
This course can also be studied online and can be studied off-shore by overseas students.
Entry Requirements
AQF level 7 bachelor degree; or at least 5 years relevant industry experience in IT or Data Science/Data Analytics; or equivalent
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Unlock a world of potential with the Master of Data Science at JCU and become an authority in the roaring big-data industry. Develop innovative solutions to contemporary problems in data science and mastermind database systems, programs, models, and projects.

JCU students have the advantage of learning how to apply data science skills to tropical, regional, and Aboriginal and Torres Strait Islander contexts. Benefit from industry expertise with courses taught by data scientists, SAS partnership and certification, and access to the SAS data Science Academy. Domestic students can choose to complete the Master of Data Science online.

Enhance your employability and advance your career in Australia and globally through the Masters Employability Program. Complete a structured co-curricular employability skills and development program, which runs for the duration of the degree. This includes a tailored plan to support individual employment objectives, beginning from semester one through to graduation.

Learn to exercise your professional judgment to suit specific circumstances and have the opportunity to complete a substantial research-based project. Your capstone project will allow you to build a portfolio to showcase your expertise.

Upon graduating, you will be across recent developments and modern challenges in data science and equipped with skills in key areas including machine learning, data mining, algorithm development, and advanced modelling.

You will have senior industry contacts, experience with real-world projects, and a foundational understanding of technology that allows you to adapt to every innovation. You will know when and how to apply computing languages and computational tools for data acquisition, queries, management, analysis, and visualisation.

You'll experience an innovative delivery method - this degree is broken up into twelve study periods. Students must complete an additional subject externally (online) in specified study periods throughout the course duration, in order to complete sixteen subjects in two, full-time years of study.
Additional information

About JCU's Master of Information and Data Science in Queensland

Be ready for the jobs of the future with a Master of Data Science (similar to a Masters in Data Analytics) from James Cook University. Deepen your knowledge of cutting-edge techniques, industry best practices, and key research methods to progress your current career or open up new opportunities for success.

Your World-Class Education Begins Here

Build your portfolio and professional network as you study your Master of Data Science degree online or in Cairns, Queensland. Work with, and learn from, leading data scientists in cutting-edge research facilities. Build your industry contacts and connect with peers who could become key professional contacts in the future.

Study under lecturers committed to student success and in subjects with small class sizes. Master the newest innovations in the big-data industry as you grow your skills and practice applying them in real-world settings. Choose to study on campus in Cairns or online.

Be Prepared to Meet Statistical Challenges

Build a solid foundation for success as you study core subjects. Become adept at gathering information and analysing algorithms, then interpreting them at a conceptual level. Gain advanced knowledge of the principles of statistical methods, linear modelling, and data visualisation.

Strengthen your understanding of the mathematics necessary for Data Scientists and how to apply these to binary relations and data science problems. Learn the latest data mining and machine learning techniques and understand how to make strategic decisions that advance business success or solve issues for society.

Master real-world problems

Focus your knowledge and learn advanced skills as you progress your data science masters degree.

Complete a capstone project to culminate your studies. Showcase your advanced skills and ability to apply complex data to real-world problems facing society, industry and science. Conceptualise problems in a working environment and then plan and implement solutions that solve them.

Study a Masters Degree in Data Analytics and Develop as a Thinker

Gain more than just knowledge and industry-specific skills through your information and data science master degree. Develop your skills as an independent thinker and as an advanced, analytical problem solver. Take the initiative to solve problems quickly and efficiently. Apply your knowledge and skills in a variety of social contexts as you gain experience in Australia's unique regional and cultural contexts.

Become an expert at working with ethical issues of privacy and data security in a way that conforms to regulatory requirements and respects cultural frameworks. Develop your skills as an effective communicator and express your ideas to experts and non-specialist audiences alike. Collaborate with others and use your data science skills in team settings as a team-member or a leader.

Get Ahead With a Master of Data Science From JCU

Your masters coursework at James Cook University will prepare you to make a difference in society, as it allows you to work for governments, the private sector or research institutes. Use machine learning to advance business intelligence for the world's leading tech and finance companies or freelance as a business intelligence specialist. Invest in your future today with a degree from JCU.
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Find out more about studying the Master of Data Science online.

Consult the handbook for more information.

Nested Qualifications

Students taking the Master of Data Science have the option to exit the course early and receive a Graduate Certificate of Data Science after four subjects or a Graduate Diploma of Data Science after eight subjects.

What you need to know before you apply

Certified copies of supporting documents

You must supply the following information with your application:

  • Previous and current certificates and academic transcripts
  • The Grading Scale used at the institution(s) where you have undertaken your studies
  • English proficiency test results (if required and available at time of application)
  • Your passport to confirm your name and citizenship (if available at time of application)

You can speed up the application process by emailing copies of your documents to If your application is approved you must then post certified copies and/or documents to:

James Cook International
James Cook University
Townsville QLD 4811, AUSTRALIA

If your documents are in a language other than English, you must provide both certified translations and a certified copy of the original document.

An acceptable certified document is a photocopy of the original document, signed and certified as a copy of the original by a public notary, registered agent of JCU, or a representative of the institution. Copies of certified copies are not acceptable.

Credit and Articulation

Before applying for credit for previous studies you should read the Credit and Articulation Procedure. You can review any possible credits you may have with our Credit Calculator. When you apply for credit you must submit the course syllabi (subject outline) for each relevant subject and ensure the subject corresponds to a similar JCU subject.

Entry requirements

As well as having the prerequisites for this course, you must also meet minimum academic and language requirements.

Check the minimum English language proficiency requirements for this course in the Course Handbook.

If you meet the academic requirements for this course, but not the minimum English requirements, you will receive a packaged offer. This includes the opportunity to take an English language program as well as an offer to study a degree at JCU. Your JCU degree offer will be conditional on you gaining a certain grade in your English program.

Application deadlines

  • 31 January for commencement in teaching period 1 (semester 1)
  • 30 June for commencement in teaching period 2 (semester 2)

Our campuses in Singapore and Brisbane operate on a trimester system – application deadlines vary for Singapore and Brisbane. View academic calendars.

How to apply

Gather electronic copies of your documentation, including an Application for Credit form, if relevant.

Register using your full legal name as it appears on your passport.

Complete all questions, upload all documents, and submit your application. You may wish to include a second course preference.

Ready to apply? Apply now.

Help with your application

If you need help with your application, or would like to change your preferences (e.g. course, campus, commencing semester) after you have submitted your application please contact JCU International Admissions at or phone: +61 7 4781 5601

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Master of Data Science

Handbook year


Course code


Course type

Masters Degree (Coursework) (AQF Level 9)


Tropical Environments and Societies

Award Requirements

Admission Requirements

Course pre-requisites

Completion of an AQF level 7 bachelor degree; or

Five (5) years or more relevant industry experience in IT or Data Science/Data Analytics; or

Other qualifications or practical experience recognised by the Dean, College of Science and Engineering as equivalent to the above.

Entry requirements for this course are consistent with the Pathways to Qualifications in the Australian Qualifications Framework (AQF level 9) Guidelines for Masters degrees.

Minimum English language proficiency requirements

Applicants of non-English speaking backgrounds must meet the English language proficiency requirements of Band 2 Schedule II of the JCU Admissions Policy.

Additional admission requirements

Mathematics B (or equivalent that includes algebra and elementary differential calculus) together with some background in computing, data analysis or programming is assumed.

Admission based on relevant industry experience must be supported by a detailed CV and proof of work experience (e.g. a letter from an employer detailing the position and job description).

Special admission requirements

Candidates will need to ensure that they have reliable access to internet services and computing resources.

Academic Requirements for Course Completion

Credit points

48 credit points as per course structure

Additional course rules

Not Applicable

Post-admission requirements

Computer and internet access is required.

Additional completion

Not Applicable

Course learning outcomes

On successful completion of the Master of Data Science, graduates will be able to:

  • Integrate and apply an advanced body of practical, technical, and theoretical knowledge, including understanding of recent developments and modern challenges, in Data Science and its application.
  • Retrieve, analyse, synthesise and evaluate complex information, concepts, methods, or theories from a range of sources.
  • Plan and conduct appropriate investigations of data sets by selecting and applying qualitative and quantitative methods, techniques and tools, as appropriate to the data and the application.
  • Analyse requirements, and demonstrate effective applications of appropriate computing languages and computational tools for data acquisition, queries, management, analysis and visualisation.
  • Identify, analyse and generate solutions for complex problems, especially related to tropical, regional, or Indigenous contexts, by applying knowledge and skills of data science with initiative and expert judgement.
  • Communicate data concepts and methodologies of data science as well as the arguments and conclusions of the application of data science, clearly and coherently to specialist and non-specialist audiences through advanced written and oral English language skills and a variety of media.
  • Critically review ethical principles, issues of data security and privacy, and where appropriate regulatory requirements and cultural frameworks to work effectively, responsibly and safely in diverse contexts.
  • Reflect on current skills, knowledge and attitudes to manage their professional learning needs and performance, autonomously and/or in collaboration with others.
  • Apply knowledge of research principles, methods, techniques and tools to plan and execute a substantial research-based project, capstone experience and/or piece of scholarship.

Course Structure (JCU Online)



MA5800:03 Foundations for Data Science

MA5820:03 Statistical Methods for Data Scientists

MA5830:03 Data Visualisation

CP5804:03 Database Systems


CP5805:03 Programming and Data Analytics Using Python

MA5801:03 Essential Mathematics for Data Scientists

MA5810:03 Introduction to Data Mining

MA5821:03 Visual Analytics for Data Scientists using SAS


MA5851:03 Data Science Master Class 1

MA5831:03 Advanced Data Management and Analysis using SAS

MA5832:03 Data Mining and Machine Learning

MA5840:03 Data Science and Strategic Decision Making for Business


CP5806:03 Data Information: Management, Security, Privacy and Ethics

MA5852:03 Data Science Master Class 2

MA5853:03 Data Science Project 1

MA5854:03 Data Science Project 2

Course Structure (Cairns)


MA5800:03 Foundations for Data Science

MA5820:03 Statistical Methods for Data Scientists

MA5830:03 Data Visualisation

CP5804:03 Database Systems

CP5805:03 Programming and Data Analytics Using Python

MA5890:03 Professional Employability

MA5810:03 Introduction to Data Mining

MA5821:03 Visual Analytics for Data Scientists using SAS

MA5851:03 Data Science Master Class 1

MA5831:03 Advanced Data Management and Analysis using SAS

MA5891:03 Professional Placement/Internship 1

MA5840:03 Data Science and Strategic Decision Making for Business

CP5806:03 Data Information: Management, Security, Privacy and Ethics

MA5852:03 Data Science Master Class 2

MA5832:03 Data Mining and Machine Learning

MA5892:03 Professional Placement/Internship 2




JCU Online

This course is 100% online through a carousel delivery model


A full-time student will study up to 25% of this course online


Expected time to complete

32 months of continuous study for JCU Online students,

24 months full time for on-campus students; or equivalent part time

Maximum time to complete

5.5 years

Maximum leave of absence

2 years


Course progression requisites

Must successfully complete carousels 1, 2 and 3 sequentially before attempting any carousel 4 subjects.

To ensure satisfactory progression a minimum of three subjects must be taken in any 12-month period.

Course includes mandatory professional placement(s)

There are no mandatory placements for students admitted to the JCU Online campus.

This course includes prescribed professional placements for students admitted to the Cairns Campus only. Students may be required to undertake such placements away from the campus at which they are enrolled, at their own expense.

Special assessment requirements


Professional accreditation requirements


Maximum allowed Pass Conceded (PC) grade




Students may apply for a credit transfer for previous tertiary study or informal and non-formal learning in accordance with the Credit Transfer Procedure.

Credit may be granted for the following:

  • An AQF Level 7 qualification in a cognate* discipline – up to 12 credit points from Carousel 1 and 2.
  • Five (5) years or more relevant industry experience in IT or Data Science/Data Analytics – up to 12 credit points from Carousel 1 and 2

Note: If relevant industry experience without qualifications in a quantitative discipline, is used to meet entry requirements, that experience will not also be used to give credit.

* Cognate disciplines include data science, computer science, IT, mathematics, statistics, engineering, physics, economics or finance.

Maximum allowed

24 credit points, except where a student transfers from one JCU award to another, then credit may be granted for any subjects where there is subject equivalence between the awards.


Credit will be granted only for studies completed in the 10 years prior to the commencement of this course.


Credit gained for any subject shall be cancelled 15.5 years after the date of the examination upon which the credit is based if, by then, the student has not completed this course.

Other restrictions

Credit will not be granted for undergraduate studies or work experience used to gain admission to the course when assessed separately for admission requirements.

Award Details

Award title


Approved abbreviation


Inclusion of majors on testamur

Not applicable – this course does not have majors

Exit with lesser award

Students who exit the course prior to completion, and have successfully completed 12 credit points of appropriate subjects, may be eligible for the award of Graduate Certificate of Data Science.

Students who exit the course prior to completion, and have successfully completed 24 credit points of appropriate subjects, may be eligible for the award of Graduate Diploma of Data Science.

Course articulation

Not applicable

Special awardsWhere coursework is completed at a grade point average of 6 or above, the Deputy Vice Chancellor, on the recommendation of the College Dean of Science and Engineering may recommend the award of Master of Data Science with Distinction

Annual Tuition Fee: AUD$32,280 (Estimate only)

Course fees are charged per year of full-time study. International course fees are reviewed annually and subject to change.

A Student Services and Amenities Fee is payable per subject up to a maximum amount per year.

Student Visa holders must have Overseas Student Health Cover (OSHC) for the duration of their Student Visa (except Norwegian, Swedish and Belgian citizens). Costs depend on the length of study and the number of dependents accompanying the student. For more information see Overseas Student Health Cover (OSHC).

Scholarships and financial aid are also available for international students.

Consult the admission requirements section in the Handbook for prerequisites and pathways into this course.

Lecturers committed to student success

The value of data lies in the ability to translate actionable knowledge and intelligence. Gain constantly evolving, cutting-edge skills and be informed and integrated through direct industry involvement with this degree.

Prof Ron White