Admission Requirements
Entry Requirements
Post Admission Requirements
Course Handbook Notes
This course is suspended and is not eligible for direct admission.
Learning Outcomes
Upon completion of this course, graduates will be able to:
1.
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.
2.
Retrieve, analyse, synthesise and evaluate complex information, concepts, methods, or theories from a range of sources.
3.
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.
4.
Analyse requirements, and demonstrate effective applications of appropriate computing languages and computational tools for data acquisition, queries, management, analysis and visualisation.
5.
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.
6.
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.
7.
Respond appropriately to issues of data security, privacy and, where appropriate, regulatory requirements and cultural frameworks to work effectively, responsibly and safely in diverse contexts.
8.
Reflect on current skills, knowledge and attitudes to manage their professional learning needs and performance, autonomously and/or in collaboration with others.
9.
Apply knowledge of research principles, methods, techniques and tools to plan and execute a substantial research-based project.
Structure
Structure
Core Subjects 36 Credit Points
Credit
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 Expiry & Other Restrictions
Credit gained for any subject shall be cancelled 14.5 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 … For more content click the Read More button below.
Maximum Credit Allowed & Currency
12 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 … For more content click the Read More button below.
An AQF Level 7 qualification in a cognate* discipline – up to 12 credit points from sequence 1 and 2.
Five (5) years or more relevant industry experience in IT or Data Science/Data Analytics – up to 12 credit points from sequence 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.