Melbourne Institute of Technology (MIT)

Structure

The Master of Data Analytics requires 9 core units and three electives from the IoT Data Analytics or Cloud Networks. A full time study load is 60 credit points per trimester. Successful completion of the course requires 240 credit points, made up of 12 units of 20 credit points.

Subjects

• AIM100 Academic Integrity Module
• MDA511 Mathematical and Statistical Methods
• MDA512 Data Science
• MDA513 ICT Practices
• MDA521 Data Security and Privacy
• MDA522 Artificial Intelligence (Prerequisite: MDA512 Data Science)
• MDA611 Predictive Analytics (Prerequisite: MDA511 Mathematical and Statistical Methods)
• MDA691 Project Management and Research Methods (Prerequisite: 4 Core units)
• MDA621 Software Practice for Big Data Analytics (Prerequisite: MDA512 Data Science)
• MDA692 Data Analytics Capstone Project (Prerequisite: MDA691 Project Management and Research Methods)
• MDA541 IOT and Sensor Networks
• MDA641 Smart Environments (Prerequisite: MDA541 IOT and Sensor Networks)
• MDA642 IoT Data Analytics Platforms (Prerequisite: MDA541 IOT and Sensor Networks)
• MN503 Overview of Internetworking
• ME605 Cloud Engineering (Prerequisite: MN503 Overview of Internetworking)
• MN622 Software Defined Networking (Prerequisite: MN503 Overview of Internetworking)

Entry requirements

• Successful completion of Australian Bachelor degree or equivalent.
• For the cognate stream: An Australian bachelor degree or equivalent in Information Technology or a related discipline such as computer science, software engineering, computer engineering or networking.
• For the non-cognate stream: An Australian bachelor degree or equivalent in any other discipline.