Fast Facts
Commencing
- Cairns: March, September
- Brisbane: March, July, November
Fees
$30,192.00^
^estimated annual tuition fee for a full-time study load
Plus Student Services and Amenities fee
Fee deferral and scholarships available if eligible
Duration
2 years full-time
Entry Requirements
AQF level 7 bachelor degree; or minimum five years relevant industry experience in IT or Data Science/Data Analytics; or equivalent
Course Code
300604
Course detail
·¬ÇÑÉçÇø 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 . Domestic students can choose to complete a .
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.
About ·¬ÇÑÉçÇø's Master of Information and Data Science in Queensland
Be ready for the jobs of the future with a Master of Data Science (Professional) (similar to a Masters in Data Analytics) from ·¬ÇÑÉçÇø. 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 (Professional) 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 (Professional) From ·¬ÇÑÉçÇø
Your masters coursework at ·¬ÇÑÉçÇø 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 ·¬ÇÑÉçÇø.
Consult the handbook for more information.
Nested Qualifications
Students taking the Master of Data Science (Professional) have the option to exit the course early and receive a after four subjects or a after eight subjects.
Inherent requirements
Inherent requirements are the identified abilities, attributes, skills, and behaviours that must be demonstrated, during the learning experience, to successfully complete a course. These abilities, attributes, skills, and behaviours preserve the academic integrity of the University’s learning, assessment,and accreditation processes, and where applicable, meet the standards of a profession. For more information please review the inherent requirements for the Master of Data Science (Professional).
·¬ÇÑÉçÇø Data Science (Professional) graduates are highly skilled specialists with invaluable professional expertise.
Graduates benefit from rapidly increasing job openings across the data industry and a data-driven future. You can apply data science to industrial, environmental, cultural, societal, and agricultural projects.
You could find work as a data scientist, data engineer, data analyst, data architect, visualisation specialist or statistician.
Handbook year | Information valid for students commencing in 2024. |
Course code | 300604 |
Course type | MCW – Masters by Coursework (AQF Level 9) |
Owner | Academy |
College | Science and Engineering |
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 ·¬ÇÑÉçÇø 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 (Professional), graduates will be able to:
|
Inherent Requirements
Inherent Requirements | Inherent requirements are the identified abilities, attributes, skills, and behaviours that must be demonstrated, during the learning experience, to successfully complete a course. These abilities, attributes, skills, and behaviours preserve the academic integrity of the University's learning, assessment, and accreditation processes, and where applicable, meet the standards of a profession. For more information please visit: Master of Data Science (Professional). |
Reasonable adjustments | All ·¬ÇÑÉçÇø students have the opportunity to demonstrate, with reasonable adjustments where applicable, the inherent requirements for their course. For more information please visit: Student Disability Policy and Procedure. |
Course Structure
CORE SUBJECTS
:03 Foundations for Data Science
:03 Statistical Methods for Data Scientists
:03 Data Visualisation
:03 Database Systems
:03 Programming and Data Analytics Using Python
:03 Career Planning
:03 Introduction to Data Mining
:03 Visual Analytics for Data Scientists using SAS
:03 Data Science Master Class 1
:03 Advanced Data Management and Analysis using SAS
:03 Professional Placement/Internship 1
:03 Data Science and Strategic Decision Making for Business
:03 Data and Information: Management, Security, Privacy and Ethics
:03 Data Science Master Class 2
:03 Data Mining and Machine Learning
:03 Professional Placement/Internship 2
Location
COURSE AVAILABLE AT | NOTES |
·¬ÇÑÉçÇø Cairns | A full-time student will study up to 25% of this course online |
| ·¬ÇÑÉçÇø Brisbane |
Candidature
Expected time to complete | 2 years full-time for on-campus students; or equivalent part-time |
Maximum time to complete | 4 years |
Maximum leave of absence | 2 years |
Progression
Course progression | To ensure satisfactory progression a minimum of three subjects must be taken in any 12 month period. |
Course includes mandatory professional placement(s) | This course includes prescribed professional placements for students admitted to the ·¬ÇÑÉçÇø Cairns and ·¬ÇÑÉçÇø Brisbane 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 | Nil |
Professional accreditation | 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:
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 ·¬ÇÑÉçÇø 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 subjects 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 (PROFESSIONAL) |
Approved abbreviation | MDataSc(Prof) |
Inclusion of majors on | 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. Students who exit the course prior to completion, and have successfully completed 36 credit points of appropriate subjects, may be eligible for the award of Master of Data Science. |
Course articulation | Not applicable |
Special awards | Students may receive an Award of Recognition in accordance with the Recognition of Academic Excellence Procedure |
Estimated annual tuition fee: $AUD30,192.00
A Student Services and Amenities fee is payable per subject up to a maximum amount per year.
A variety of Scholarships are available to suit different student types.
·¬ÇÑÉçÇø offers multiple Pathways to University. If you do not meet the entry requirements for this course, consider exploring our available Pathways options.
Contact our friendly team today to discover which pathway is right for you.
Complete an online application through our
Real stories
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Lecturer
Dr Kelly Trinh
Associate Lecturer, Statistics and Data Science
·¬ÇÑÉçÇø Master of Data Science students develop the knowledge and skills to work with machine learning algorithms and statistical techniques widely applied in practice. Students have hands-on experience working with a range of programming languages such as Python, R, Cloud Computation (Amazon Web Services) and SAS.