Master of Data Science

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Master of Data Science

Location
Cairns
This course can also be studied online.
Commencing
March, September
Duration
2 years full time
Part-time available
This course is delivered in four discrete parts.
Attendance mode
Internal
This course can also be studied online.
Entry Requirements
AQF level 7 bachelor degree; or at least 5 years relevant industry experience in IT or Data Science/Data Analytics; or equivalent
QTAC Code
Not applicable
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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.

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. During each study period, one subject is completed on campus. International student visa holders are required to 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

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.

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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The Master of Data Science is offered from JCU’s Cairns City campus.

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.

Visit the Graduate Research School Prospective Students website for more information, and then complete an online application through our Online Application Portal.

  • Handbook

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Master of Data Science

Handbook year

2020

Course code

300104

Course type

Masters Degree (Coursework) (AQF Level 9)

Division

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
requirements

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

CORE SUBJECTS

CAROUSEL 1

MA5800:03 Foundations for Data Science

MA5820:03 Statistical Methods for Data Scientists

MA5830:03 Data Visualisation

CP5804:03 Database Systems

CAROUSEL 2

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

CAROUSEL 3

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

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

CAROUSEL 4

MA5851:03 Data Science Master Class 1

MA5852:03 Data Science Master Class 2

MA5853:03 Data Science Project 1

MA5854:03 Data Science Project 2

Campus

COURSE AVAILABLE AT

NOTES

JCU Online

This course is 100% online through a carousel delivery model.

Cairns

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

Candidature

Expected time to complete

32 months in continuous carousel mode (48CP) 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

Progression

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)

No

Special assessment requirements

Nil

Professional accreditation requirements

Nil

Maximum allowed Pass Conceded (PC) grade

Nil

Credit

Eligibility

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.

Currency

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

Expiry

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

MASTER OF DATA SCIENCE

Approved abbreviation

MDataSc

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

Student Services and Amenities fee is also payable per subject up to a maximum amount per year.

A variety of Scholarships are available to suit different student types.

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