Master of Data science
This course equips students with skills to work in data science related areas such as the health care, finance, government administration and IT industries.
OVERVIEW
CRICOS code 104808F
Duration (Full Time) 2 Years
Course Fees
Intake Dates March, July, November Students Only available to international students Faculty Institute of Innovation, Science and Sustainability
Campus Melbourne, SYDNEY
Entry Requirements
English Language Requirement
Overall IELTS (Academic) band score of 6.0 with no individual band score less than 6.0, or equivalent.
Academic Entry Requirements
Successful completion of Australian Bachelor degree in science, mathematics, statistics, engineering, information technology or business; or Overseas Equivalent.
Students will be required to demonstrate they have previously studied introductory mathematics and at least one information technology course in their undergraduate degree. If they cannot, they must select an approved elective course in their first semester of study to meet prerequisite requirements.
COURSE OUTLINE
This program provides an opportunity for you to develop an advanced understanding of data science by incorporating and interpreting complex information, concepts and theories to relevant disciplines, using data science tools and methods to manage, process, and analyse data.
Throughout the program, you will utilise your skills to handle large volumes of data, working with real-time data, cloud computing, unstructured data and statistical models.
As a graduate, you may work in data science related areas such as the health care, finance, government administration and IT industries.
Career opportunities
- Data Scientist
- Statistician
- Data engineer
- Data warehouse operator
- Business analyst
Sample Study Program*
Year
Semester 1
Semester 2
1
- Data Science for All
- Artificial Intelligence and Machine Learning
- Statistics and R
- Professional Research and Communication
- Foundations of Programming
- Elective
- Elective
- Elective
2
- Advanced Data Science Project 1
- Advanced Data Science Project 2
- Experiment Design and Visualisation
- Data Analytics for Cyber Threat Intelligence
- Computational Methods for Data Analysis
- Regression and Multivariate Data Analysis
* This is sample structures only. Please refer to course offerings for more detail.
* Unit offering may change during semester subject to staff availability.
CONTACT HOURS
Contact hours can vary depending on requirements, however typical contact hours for full-time study are around 25-30 hours comprising of on-campus classes, online learning and self-directed study.
RECOGNITION OF PRIOR LEARNING
International students wishing to apply for credit exemption are required to indicate on the application form that you they wish to be considered for credit exemption and provide a syllabus of their previous studies with their application for the course. Applications will then be assessed for eligibility for credit exemption into the FedUni course. Not all courses offer credit exemption.
ADDITIONAL INFORMATION
To help you get the most from your online learning experience, it’s important that you own or have frequent access to a fast and reliable computer that’s ideally not more than two years old.
You will also need frequent access to a reliable high-speed internet connection. You should expect to use approximately 5GB of data each month, per unit, just for study use.
For further information, visit the Minimum IT requirements for studying with us webpage.
Look for further information on the course through FedUni Course Finder: https://study.federation.edu.au/
FedUni CRICOS Code 00103D | ATMC CRICOS Code 03013D