Graduate Certificate of Data Science

300111 - Graduate Certificate of Data Science

Graduate Diploma of Data Science

300106 - Graduate Diploma of Data Science

Master of Data Science (Professional)

300604 - Master of Data Science (Professional)

MASTER OF DATA SCIENCE

MA5830 or CC5902

Sequence 1 

Students who have taken CC5902:03 IoT Communication Systems must select MA5830:03 Data Visualisation.

MA5821 or MA5830

Students who have taken CC5902:03 IoT Communication Systems must select CC5904:03 IoT Security and Cloud Computing.

MA5801 or CC5904

Students who have taken CC5902:03 IoT Communication Systems must select CC5903:03 IoT Edge Devices, CC5904:03 IoT Security and Cloud Computing, and MA5830:03 Data Visualisation.

CP5805 or CC5903

Sequence 2

Students who have taken CC5902:03 IoT Communication Systems must select CP5805:03 Programming and Data Analytics Using Python.

MA5831 or CP5805

Sequence 3 

Core Subjects 

Structure

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.

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.

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.

Retrieve, analyse, synthesise and evaluate complex information, concepts, methods, or theories from a range of sources.

Analyse requirements, and demonstrate effective applications of appropriate computing languages and computational tools for data acquisition, queries, management, analysis and visualisation.

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.

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.

Apply knowledge of research principles, methods, techniques and tools to plan and execute a substantial research-based project.

Reflect on current skills, knowledge and attitudes to manage their professional learning needs and performance, autonomously and/or in collaboration with others.

300504

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).

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). Offerings: All

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.

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. Offerings: All

Applicants of non-English speaking backgrounds must meet the English language proficiency requirements of ”Band 2” – <a href="https://www.jcu.edu.au/policy/procedures/student-services-procedures/admissions-policy-schedule-ii">Schedule II</a> of the JCU Admissions Policy.

Applicants of non-English speaking backgrounds must meet the English language proficiency requirements of ”Band 2” – <a href="https://www.jcu.edu.au/policy/procedures/student-services-procedures/admissions-policy-schedule-ii">Schedule II</a> of the JCU Admissions Policy. Offerings: All

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: <a href="https://www.jcu.edu.au/inherent-requirements/master-of-data-science-inherent-requirements">Master of Data Science</a>. All JCU students have the opportunity to demonstrate, with reasonable adjustments where applicable, the inherent requirements for their course. For more information please visit: <a href="https://www.jcu.edu.au/policy/student-services/student-disability">Student Disability Policy and Procedure</a>.

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: <a href="https://www.jcu.edu.au/inherent-requirements/master-of-data-science-inherent-requirements">Master of Data Science</a>. All JCU students have the opportunity to demonstrate, with reasonable adjustments where applicable, the inherent requirements for their course. For more information please visit: <a href="https://www.jcu.edu.au/policy/student-services/student-disability">Student Disability Policy and Procedure</a>. Offerings: All

Computer and internet access are required.

Computer and internet access are required. Offerings: All

Course and Subject Handbook

300504 - Master of Data Science