GD-PREDAN v.2 Graduate Diploma in Predictive Analytics
Curtin University
About
Graduate Diplomas prepare students to develop advanced knowledge and skills for professional or highly skilled work and further learning corresponding to AQF level 8 qualifications.
Graduate Diploma 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 Diploma course is designed over one year study to provide students with an in-depth background to predictive analytics and the use of computing, including basic concepts of data analysis, computing and visualisation, as well as in-depth understandings on data security, data mining and business applications.
Additional Course Expenses
Students may be expected to purchase a number of textbooks and other essential study materials.
Structure
Graduate Diplomas contain a series of units which may include compulsory (core), optional or elective units to cater for student preferences. They may contain a range of majors/streams for students to choose from to pursue learning in a specialised area of study.
Course Learning Outcomes
A graduate of this course can:
1. assess the theoretical background basis of data analytics and data processing of unstructured data to produce a qualified interpretation of the data
2. evaluate the various approaches to data analysis and develop a strategy for adapting them to a specific situation
3. evaluate and synthesise information from a variety of sources and develop a plan to optimise data management, processing and prediction
4. communicate effectively with a wide range of people from different discipline areas, professional positions and countries; able to communicate data analysis findings in a variety of ways via written, verbal or electronic communications
5. evaluate and select appropriately from existing and emerging data analysis and prediction technologies
6. engage in continual updating of knowledge with regard to new and emerging prediction analysis concepts, issues and management strategies
7. evaluate, interpret and apply the international standards related to the predictive analytics industry. Solve problems with a global perspective
8. identify the ethical issues related to protecting the rights of individuals from diverse cultures including 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 in all areas of prediction design, demonstrating leadership and ethical behaviour at all times
Duration and availability
This course is one year full-time or the equivalent part-time.
Location and delivery Mode
YEAR | LOCATION | PERIOD | ALL | INTERNAL | PARTIALLY ONLINE INTERNAL | EXTERNAL | FULLY ONLINE |
---|---|---|---|---|---|---|---|
2021 | Bentley Perth Campus | Semester 1 | Y | ||||
2021 | Bentley Perth Campus | Semester 2 | Y | ||||
2022 | Bentley Perth Campus | Semester 1 | Y | ||||
2022 | Bentley Perth Campus | Semester 2 | 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
Code | Version | Course Name | HRS/WK | Credit |
---|---|---|---|---|
ECOM5002 | v.2 | Business Quantitative Techniques | 3.0 | 25.0 |
OR | ||||
COMP5005 | v.1 | Fundamentals of Programming | 4.0 | 25.0 |
ISYS5007 | v.1 | Data Management | 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 |
100.0 |
YEAR 1 SEMESTER 2
Code | Version | Course Name | HRS/WK | Credit |
---|---|---|---|---|
MGMT5007 | v.1 | Management and Organisational Behaviour | 2.0 | 25.0 |
COMP5008 | v.1 | Data Structures and Algorithms | 4.0 | 25.0 |
COMP5009 | v.1 | Data Mining | 3.0 | 25.0 |
COMP5005 | v.1 | Fundamentals of Programming | 4.0 | 25.0 |
OR | ||||
ECOM5002 | v.2 | Business Quantitative Techniques | 3.0 | 25.0 |
100.0 |
Entry requirements
Applicants for a Graduate Diploma are required to meet University academic and English language entry standards; details are provided at http://study.curtin.edu.au/. Applicants generally require a Bachelor Degree or Graduate Certificate. 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/non-school-leavers/rpl.cfm
Intermediate Awards
A student who has successfully completed the requirements of an approved intermediate award may apply for graduation in that award subject to approval of Head of School/Department. Fees apply. Intermediate awards approved for this course:
GC-PREDAN Graduate Certificate in Predictive Analytics
Pathway to Further Study
Graduates may qualify for entry to some Master degrees. For further details, see the University website http://curtin.edu.au.
Institution
