GC-PREDAN v.1 Graduate Certificate in Predictive Analytics
Course CRICOS Code: 092979A
Registered full-time Duration: 0.5 Years
Graduate Certificates prepare students to develop advanced knowledge and skills for professional or highly skilled work and further learning corresponding to AQF level 8 qualifications.
The Graduate Certificate in Predictive Analytics is designed to prepare you for entry to the multi-disciplinary Predictive Data Analytics profession, in which many operations are automated and controlled remotely. Predictive Analytics is the study of data in order to predict and subsequently optimise management decisions. The Graduate Certificate in Predictive Analytics is designed for students who wish to learn the basics of predictive data analytics, providing basic concepts of data analysis, computing and visualisation.
Additional Course Expenses
Students may be expected to purchase a number of textbooks and other essential study materials.
Course Entry and Completion Details
Applicants for a Graduate Certificate are required to meet University academic and English language entry standards; details are provided at http://futurestudents.curtin.edu.au. Applicants generally require a Bachelor Degree or equivalent credit gained for recognised learning. Any specific course entry and completion requirements must also be met.
Specifically, students require a Bachelor's Degree.
Credit for Recognised Learning
Applications for credit towards a course are assessed on an individual basis. Credit reduces the amount of learning required to complete the course and may be granted for formal education qualifications, non-formal learning from non-award programs of study and informal learning through work experiences. Further information can be found at http://futurestudents.curtin.edu.au.
Pathway to Further Study
Graduates may qualify for entry to some Graduate Diplomas and Master degrees. For further details, see the University website http://curtin.edu.au.
Students who successfully complete this course may be eligible for entry into the GD-PREDAN Graduate Certificate in Predictive Analytics; MC-PREDAN Master of Predictive Anlytics, to further their studies.
Graduate Certificates contain a series of units which may include compulsory (core), optional or elective units to cater for student preferences.
Course Learning Outcomes
A graduate of this course can:
1. comprehend the theoretical background of data analytics and data processing of unstructured data for correct interpretation of the data
2. explain the various approaches to data analysis and appreciate strategies for adapting them to a specific situation
3. assess information from a variety of sources and assisting to develop a plan to optimise data management, processing and prediction
4. communicate data analysis findings in a variety of ways via written, verbal or electronic communications
5. assist in evaluating and selecting appropriately from existing and emerging data analysis and prediction technologies
6. utilise fundamental knowledge to enable further study of new and emerging prediction analysis concepts, issues and management strategies
7. identify the international standards related to the predictive analytics industry; consider issues with a global perspective
8. articulate the ethical issues related to protecting the rights of individuals from diverse cultures; inclusive of Indigenous perspectives and how that maps to ensuring the quality and integrity of data collected and analysed
9. apply lessons learnt in a professional manner to assist in all areas of prediction design, demonstrating leadership and ethical behaviour at all times
Duration and Availability
This course is 6 months' full-time or the equivalent part-time study.
Location and delivery Mode
|Year||Location||Period||All*||Internal||Partially Online Internal^||External||Fully Online#|
|2017||Bentley Campus||Semester 1||Y|
The information displayed above refers to study periods and locations where the course is available for first time entry. Students are normally only offered or admitted to a course once.
* The course itself may not be available either solely internally or externally but individual units may be offered in either or both of those modes. Prospective students should contact the Course Coordinator for further information.
^ Course and associated units are offered in this mode permitting International Onshore student enrolment.
# Course and associated units are offered in this online only mode and DO NOT permit International Onshore student enrolment.
|Year 1 Semester 1|
|COMP5005||v.1||Fundamentals of Programming||4.0||25.0|
|STAT5001||v.1 **||Statistical Probability||3.0||12.5|
|COMP5006||v.1||Introduction to Computer Systems||4.0||25.0|
|STAT5006||v.1 *||Statistical Data Analysis 1||3.0||12.5|
|ECOM5002||v.1||Quantitative Techniques for Business||3.0||25.0|
|ISEC5006||v.1||Fundamental Concepts of Data Security||3.0||25.0|
|STAT5009||v.1||Decision Methods and Predictive Analytics||3.0||25.0|
* Students taking STAT5001, must take STAT5006.
** Students taking STAT5006, must take STAT5001.
If you need more course information, you may contact the relevant areas: For Current Students: Student Services Office, please click here for further details: http://students.curtin.edu.au/contact_offices.cfm For Domestic Future Students: Future Students Centre, email: firstname.lastname@example.org Tel: +61-8-9266 1000 For International Future Students: Curtin International, email: email@example.com Tel: +61-8-9266 7331
Course Structure Disclaimer
Curtin University reserves the right to alter the internal composition of any course to ensure learning outcomes retain maximum relevance. Any changes to the internal composition of a course will protect the right of students to complete the course within the normal timeframe and will not result in additional cost to students through a requirement to undertake additional units.
Information in this publication is correct at the time of printing but may be subject to change.
In particular, the University reserves the right change the content and/or method of assessment, to change or alter tuition fees of any unit of study, to withdraw any unit of study or program which it offers, to impose limitations on enrolment in any unit or program, and/ or to vary arrangements for any program.
This material does not purport to constitute legal or professional advice.
Curtin accepts no responsibility for and makes no representations, whether express or implied, as to the accuracy or reliability in any respect of any material in this publication.
Except to the extent mandated otherwise by legislation, Curtin University does not accept responsibility for the consequences of any reliance which may be placed on this material by any person.
Curtin will not be liable to you or to any other person for any loss or damage (including direct, consequential or economic loss or damage) however caused and whether by negligence or otherwise which may result directly or indirectly from the use of this publication.
International students studying in Australia on a student visa can only study full-time and there are also specific entry requirements that must be met. As some information contained in this publication may not be applicable to international students, refer to international.curtin.edu.au for further information. Australian citizens, permanent residents and international students studying outside Australia may have the choice of full-time, part-time and external study, depending on course availability and in-country requirements.