Entry requirements
Entry requirements set by ASQA are the basic qualifications and criteria that students must meet before enrolling in a nationally recognised course.
These requirements ensure students have the skills and knowledge needed to undertake this course.
- There are no formal academic requirements
- Additional entry requirements are set by individual course providers
Course fees
The estimated fee reflects the price range across training providers in Maitland.
The course fee is determined by each individual provider and may vary depending on factors like study mode and student support availability.
Career opportunities
The Master of Applied Data Analytics will prepare you for the following roles.
Data Scientist
A Data Scientist looks for trends in data to provide information that guides organisational decisions. You might work for a retail business to prov...
Quantitative Analyst
A Quantitative Analyst applies mathematical and statistical techniques to analyse financial data and support decision-making in financial markets....
Data Analyst
A Data Analyst interprets information and uses it to improve the way a company does business. You’ll use various methods to collect information and...
Find a course provider
Compare all providers for the available in Maitland to find the right fit for you.
More about Master of Applied Data Analytics
The Master of Applied Data Analytics is an exceptional course for those looking to advance their careers in the growing fields of information technology and data science. Delivered through The University of Melbourne, this programme is available in Maitland and equips students with the skills needed to excel as professionals in roles such as Data Analyst, Data Engineer, and Data Scientist. The hands-on approach and strong theoretical foundation make it an ideal choice for those wanting to dive deeply into data analytics.
Situated in the heart of Maitland, students will benefit from the opportunity to study this innovative course within a vibrant community. The curriculum covers diverse areas, including Information Technology, Science, and Data Analytics. By integrating knowledge from Mathematics and Statistics and Data Sciences, students will emerge as well-rounded candidates prepared for various exciting roles including Quantitative Analyst and Machine Learning Engineer.