Graduate Diploma in Data Science
Enter the revolutionary area of big data where there is a strong demand for data scientists1. Vast volumes of data are generated every day around the globe. The need to make sense of it has given rise to the revolutionary area of ‘Big Data’, and to a new career of ‘data scientist’. Data scientists find patterns, making meaning and drawing value from the seeming chaos.There is an acute shortage of data scientists, with a McKinsey Global Institute report projecting a 50 per cent gap between projected demand and supply by 2018. Demand for professionals with strong data management and analytic skills is expected to grow. Taught by leading researchers you will learn to analyse and visualise rich data sources, how to spot data trends and to generate data management strategies.
This graduate diploma is offered as part of a suite of three programs (graduate certificate, graduate diploma and master). Each qualification extends to the next, so you can easily transition to a master level qualification. If you decide to exit this qualification having completed the first four courses you will receive the Graduate Certificate in Data Science. If you finish this graduate diploma and want to do further study, consider going on to the Master of Data Science.In the Graduate Diploma in Data Science you will learn current techniques in data science, and how to apply this knowledge professionally. You will develop:
- cognitive skills to review, analyse, consolidate and synthesise knowledge and identify and provide solutions to complex problems in data science
- cognitive skills to think critically and to generate and evaluate complex ideas
- specialised technical and creative skills in data science
- communication skills to demonstrate an understanding of theoretical concepts
- communication skills to transfer complex knowledge and ideas to a variety of audiences
Campus Information
Mawson Lakes
In the progressive area of Mawson Lakes just 12km north of the city, you can study civil aviation, education, engineering, environmental studies, information technology, science, and sport and recreation management.
Intakes
- Feb
- July
Application Processing Time in Days: 14
Minimum English Language Requirements
| English Level Description | IELTS (1.0 -9.0) | TOEFL IBT (0-120) | TOEFL CBT (0-300) | PTE (10-90) | |
|---|---|---|---|---|---|
| Expert | 9 | 120 | 297-300 | 86-90 | |
| Very Good | 8.5 | 115-119 | 280-293 | 83-86 | |
| Very Good | 8 | 110-114 | 270-280 | 79-83 | |
| Good | 7.5 | 102-109 | 253-267 | 73-79 | |
| Good | 7 | 94-101 | 240-253 | 65-73 | |
| Competent | 6.5 | 79-93 | 213-233 | 58-65 | |
| Competent | 6 | 60-78 | 170-210 | 50-58 | |
| Modest | 5.5 | 46-59 | 133-210 | 43-50 | |
| Modest | 5 | 35-45 | 107-133 | 36-43 | |
| Limited | 4 | 32-34 | 97-103 | 30-36 | |
| Extremely Limited | < 4 | < 31 | < 93 | < 30 |
Job Opportunity Potential
The field of data science is evolving at a rapid rate. It will continue to grow as savvy business leaders integrate analytics into every facet of their organisation. Analytics, science, data, and reasoning are becoming embedded into decision-making processes, every day and everywhere in the business world1. Careers to consider:
- data scientist: understanding interfaces, data migrations, big data and databases; taking the lead in processing raw data and determining the best types of analysis; mining large volumes of data to understand user behaviours and interactions; communicating data findings to IT leadership and business leaders to promote innovation
- big data visualiser: using visualisation software to analyse data, drawing implications and communicating findings; providing input on database requirements for reporting/analytics; acquiring, managing and documenting data (e.g. geo-spatial); creating visualisations from data or GIS data analysis
- business data analyst: working with stakeholders, analysts and senior management to understand business strategy and the questions that need to be asked; identifying research needs; designing experiments and making recommendations based on results; driving complex analytics projects to support the business
- information security analyst: reporting and producing recommendations to prevent security incidents; security control monitoring; implementing new security technology, methods and techniques; championing security best practice; reviewing systems for security disks and compliance issues
- data engineer: managing data workflows, pipelines, and ETL processes, preparing ‘big data’ infrastructure, working with data scientists and analysts
- machine learning analyst: building and implementing machine learning models, developing production software through systems in big data production pipeline, working with recommendation systems, developing customer analytics solutions
PSW Opportunity
NA
Admission Requirement / Eligibility Criteria
Applicants to the Graduate Diploma in Data Science will normally have:
- a Bachelor degree or equivalent from a recognised higher education institution with a minimum of one year of full-time study in Mathematics or Information Technology or Data Science or a combination thereof; OR
- a Graduate Certificate in Data Science or equivalent from a recognised higher education institution.
- Course Code: 079911G
- Course Type: Full Time
- Course Level: Post Graduate Diploma or Certificate
- Duration: 01 Year
-
Total Tuition Fee:
38500 AUD
Annual Cost of Living: 24505 AUD
Application Fee: N/A
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