Graduate Certificate of Data Science
Graduate Certificate of Data Science
GRC – Graduate Certificate (AQF Level 8)
Tropical Environments and Societies
Completion of an AQF level 7 bachelor degree; or
five (5) years or more of 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.
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 the employer detailing your 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
12 credit points as per course structure
Computer and internet access is required.
Course learning outcomes
On successful completion of the Graduate Certificate of Data Science, graduates will be able to:
MA5800:03 Foundations for Data Science
MA5820:03 Statistical Methods for Data Scientists
MA5830:03 Data Visualisation
CP5804:03 Database Systems
COURSE AVAILABLE AT
This course is 100% online through a carousel delivery model.
|A full-time student will study up to 25% of this course online.|
Expected time to complete
36 weeks in continuous carousel model (12cp) for JCU Online students; 6 months full time for on-campus students; or equivalent part-time
Explanation for JCU Online students – four subjects takes 32 weeks, but spanning the mid-year and end-of-year breaks will add four weeks in most years.
Maximum time to complete
Explanation – "part-time" modality for carousel offerings is not expected to be at one half of the full time rate. Because of the currency of knowledge in Data Science it is important to know if a candidate is going to complete their studies over a longer time frame, especially if they intend to continue into the Master's program. 36 weeks x 1.5 + 1 year LoA = 106 weeks. In Carousel model a leave of absence cannot be a full year if the student wishes to come back into the next subject.
Maximum leave of absence
Course includes mandatory professional placement(s)
Nil – this course is not accredited.
Maximum allowed Pass
Supplementary exam for
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: Where 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.
6 credit points except where a student transfers from one JCU award to another, then credit may be granted for more than two-thirds of the new award, 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 12 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 for work experience used to gain admission to the course when assessed separately for admission requirements.
GRADUATE CERTIFICATE OF DATA SCIENCE
Inclusion of majors on
Not applicable – this course does not have majors
Exit with lesser award
Students who complete this course are eligible for entry to the Graduate Diploma of Data Science and the Master of Data Science, and may be granted credit for all subjects completed under this course.