- Cairns: March, September
- Brisbane: January, March, May, July, September, November
2 years full-time
or part-time equivalent
AQF level 7 bachelor degree; or minimum five years relevant industry experience in IT or Data Science/Data Analytics; or equivalent
About JCU's Master of Information and Data Science in Queensland
Your World-Class Education Begins Here
Be Prepared to Meet Statistical Challenges
Master real-world problems
Study a Masters Degree in Data Analytics and Develop as a Thinker
Get Ahead With a Master of Data Science (Professional) From JCU
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).
JCU 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.
|Information valid for students commencing in 2024.|
MCW – Masters by Coursework (AQF Level 9)
Science and Engineering
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.
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
48 credit points as per course structure
Additional course rules
Computer and internet access is required.
Course learning outcomes
On successful completion of the Master of Data Science (Professional), graduates will be able to:
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).
All JCU 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.
: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
COURSE AVAILABLE AT
A full-time student will study up to 25% of this course online
Expected time to complete
2 years full-time for on-campus students; or equivalent part-time
Maximum time to complete
Maximum leave of absence
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 JCU Cairns and JCU Brisbane Campus only. Students may be required to undertake such placements away from the campus at which they are enrolled, at their own expense.
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.
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 subjects 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.
Credit will not be granted for undergraduate studies or work experience used to gain admission to the course when assessed separately for admission requirements.
MASTER OF DATA SCIENCE (PROFESSIONAL)
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.
Students may receive an Award of Recognition in accordance with the Recognition of Academic Excellence Procedure
Complete an online application through our
Dr Kelly Trinh
Associate Lecturer, Statistics and Data Science
JCU 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.