Master of Data Science

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Master of Data Science

Location
Cairns, Online
This course is offered at the JCU Cairns City campus.
Commencing
March, September
Duration
2 years full time
This course is delivered in four discrete parts.
Attendance mode
Internal
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
CRICOS code
099445G
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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.

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.

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 internationaladmissions@jcu.edu.au. 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 enquiries@jcu.edu.au or phone: +61 7 4781 5601

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Master of Data Science

Handbook year

2019

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 Advanced Statistical Methods for Data Scientists

CAROUSEL 3

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

MA5831:03 Big Data: Management and Processing

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

Advanced Standing

Eligibility

Students may apply for advanced standing for previous tertiary study in accordance with the Credit and Articulation policy and associated procedures.

Advanced standing 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 advanced standing.

* 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 advanced standing may be granted for any subjects where there is subject equivalence between the awards.

Currency

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

Expiry

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

Other restrictions

Advanced standing 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

Annual Tuition Fee: AUD$31,200 (Estimate only)

Courses are charged per year of full-time study. International course fees are reviewed annually and subject to change. You can find current fees in the undergraduate tuition fees guide.

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 dependants accompanying the student. For more information see Overseas Student Health Cover (OSHC).

Scholarships and financial aid are also available for international student.

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