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 Geelong.
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 Geelong to find the right fit for you.
More about Master of Applied Data Analytics
The Master of Applied Data Analytics is an increasingly vital course for professionals seeking to thrive in the booming digital economy. In Geelong, the University of Melbourne provides a comprehensive training programme, offering flexibility through online delivery. This qualification prepares graduates for various demanding roles such as Data Engineer, Data Scientist, and Data Analyst. By taking this course, students gain the skills to unlock the potential of data, a crucial aspect for businesses looking to improve their decision-making processes.
The curriculum for the Master of Applied Data Analytics is aligned with essential fields of study such as Information Technology, Science, Mathematics and Statistics, and Data Sciences. This interconnected approach provides a robust foundation that equips students to step into advanced careers, including roles like Machine Learning Engineer and Quantitative Analyst. Graduates are well-placed to support organisations in leveraging data analytics for strategic growth.