When you study the data you discover more than meets the eye. Data Analytics is the bridge between technology, data science and strategy.
Ever wondered how your phone knows which ads to show you at lunchtime? Or how the supermarket emails you with specials on your favourite products? It’s not a coincidence. It’s the work of data analytics encouraging you to buy more.
2 Years (4 Trimesters)
Full-Time or Equivalent Part-Time
March,
July,
November
Sydney, Melbourne
Level 9
DURATION 2 Years (4 Trimesters) Full-Time or Equivalent Part-Time | |
INTAKES March, July, November | |
LOCATION Sydney, Melbourne | |
AQF LEVEL Level 9 |
2 Years (4 Trimesters)
Full-Time
March,
July,
November
102711J, 102710K (NSW)
Sydney, Melbourne
Level 9
DURATION 2 Years (4 Trimesters) Full-Time | |
INTAKES March, July, November | |
CRICOS CODE 102711J, 102710K (NSW) | |
LOCATION Sydney, Melbourne | |
AQF LEVEL Level 9 |
The Master of Data Analytics (Major in Software Engineering) has been developed in consultation with a broad industry advisory panel. This major prepares students for a future career in various industries, because it capitalises on the intersection of two fast growing fields Data Analytics and Software Engineering. Graduates can play a crucial role in transforming businesses by applying their data analytics and software engineering skills.
The major in Software Engineering will prepare our students for the future market, studying units that focus on Software Engineering Fundamentals, Software Practice for Big Data Analytics, and Human-computer Interaction Design. They will gain an in-depth understanding of essential Software Engineering principles, Software Development Lifecycle models, Software Quality Assurance and Testing methodologies and Human-Computer Interaction. Students will learn to apply them to design and develop robust and tested software and applications. These can be used across a wide range of industries that deploy data analytics.
Graduate with the strategic knowledge and technical skills to find a rewarding job in this growing field.
Learn how to think creatively and create innovative, data driven solutions to real world problems.
Advance your understanding of AI and machine learning.
We use an academic support program called InSPIRE to tailor our learning to each student.
Our curriculum is based on solving real world problems. MIT has a strong reputation for Work-Integrated Learning.
Get in the driver's seat and take control of your learning - with flipped classrooms, you’ll arrive in class prepared and ready to build on your learning.
Graduate with the strategic knowledge and technical skills to find a rewarding job in this growing field.
Learn how to think creatively and create innovative, data driven solutions to real world problems.
Advance your understanding of AI and machine learning.
We use an academic support program called InSPIRE to tailor our learning to each student.
Our curriculum is based on solving real world problems. MIT has a strong reputation for Work-Integrated Learning.
Get in the driver's seat and take control of your learning - with flipped classrooms, you’ll arrive in class prepared and ready to build on your learning.
A career in data analytics will give you great job prospects. Roles can include:
When you study Data Analytics at MIT you’ll learn how to combine the essentials of statistics and data with technology. You’ll also develop skills such as strategic thinking, project management and problem solving.
Our industry based final year projects offer exciting opportunities to apply your learning to solve real-world problems for industry leaders.
Students have an option to specialise in:
A Major
Specialisations in
Common Core Units
Electives
The following electives are available:
The Course Coordinator may approve another elective from 500 or 600 level units, subject to meeting prerequisites.
Common Core Units
Some remarks:
Program structures and units are subject to change through the process of regular course revision. There is no guarantee that every unit will be offered in any particular trimester.
*Additional Fee
It is mandatory for the awarding of the Master of Data Analytics degree that the student undertakes the final year project units: MDA691 Project Management and Research Methods, and MDA692 Data Analytics Capstone Project. If a third party is required to find a project for the student, the student will incur a fee.
The MDA course is designed to encompass two streams, one for cognate and another for non-cognate students.
Cognate students are those that have an Australian Bachelor degree or equivalent in an Information and Communications Technology (ICT) discipline such as Computer Science, Computer Engineering, Information Technology and Software Engineering.
For the non-cognate stream, students must have an Australian Bachelor degree or equivalent in a non-ICT discipline. Because we have existing units that provide foundational ICT knowledge for our non-cognate students, we can accept a broader scope of students into our programs.
To qualify for entry you need to have;
The MDA course is designed to encompass two streams, one for cognate and another for non-cognate students.
Cognate students are those that have an Australian Bachelor degree or equivalent in an Information and Communications Technology (ICT) discipline such as Computer Science, Computer Engineering, Information Technology and Software Engineering.
For the non-cognate stream, students must have an Australian Bachelor degree or equivalent in a non-ICT discipline. Because we have existing units that provide foundational ICT knowledge for our non-cognate students, we can accept a broader scope of students into our programs.
For entry you need to have:
English Language Requirements
IELTS (Academic) 6.0 with no band less than 6.0 equivalent.
Students can gain credit for learning already achieved. Applicants are assessed on a case-by-case basis. Learn more about credit transfer. Read more about the process.
Applications for credit transfer must be made before or during orientation and enrollment week.
State of the art facilities
Study now and pay later with FEE-HELP.
Students studying at MIT may be eligible for FEE-HELP. FEE-HELP is a loan scheme that assists eligible fee-paying students to pay their tuition fees. An eligible person may borrow up to the FEE-HELP limit to pay tuition fees over their lifetime.
Read more about FEE-HELP or visit Study Assist.
Tuition Fees
For 2021-22 fee information visit the tuition fee page.
Youth and student allowances
For details on Youth Allowance, Austudy and ABSTUDY, visit Human Services.
Tuition Fees
For 2020-21 fee information visit the tuition fee page.
For further information please visit
Data Analytics is the process of analysing data, extracting insights and information on trends, finding answers to questions and insights. Data analysts create systems that gather relevant data, analyse the data and manage the data through collection, storage and retrieval.
Networking establishes the system and infrastructure, data analytics takes the data and information that the networks generate and turns it into a story. Data Analytics requires different skills in analysis and strategy from the data.
Data analysts take control of business data and make sense of it, so it can translate into strategies to drive a business forward.
They use the latest technology in Artificial Intelligence (AI), Data Science, Big Data Analytics, Visualisation, Smart Sensors and Cloud Computing to improve the way we do business.
According to Job Outlook, the salary for data analysts is higher than average. Salaries ranging from $75000 to $100000 + for highly skilled analysts. Skilled data analysts are in high demand, and the industry is expected to grow rapidly.
Before applying, make sure you:
You should provide certified copies of your academic and other essential documents at the time of application.
You must upload all requested documents at the time of the application.
Learn more about the whole of the institution set here.
Phone our friendly student recruitment team on 1800 648 669.
enquiries@mit.edu.au
Before applying, make sure you:
You must upload all requested documents at the time of the application.
If you are looking to apply for a credit transfer, you must submit the following supporting documents with your credit application:
You should provide certified copies of your academic and other essential documents at the time of application.
Offshore international students must apply through an MIT authorised agent in their home country.
Phone our friendly student recruitment team on 1800 648 669.
enquiries@mit.edu.au
When you study Data Analytics at MIT you’ll learn how to combine the essentials of statistics and data with technology. You’ll also develop skills such as strategic thinking, project management and problem solving.
Our industry based final year projects offer exciting opportunities to apply your learning to solve real-world problems for industry leaders.
Students have an option to specialise in:
A Major
Specialisations in
Common Core Units
Electives
The following electives are available:
The Course Coordinator may approve another elective from 500 or 600 level units, subject to meeting prerequisites.
Common Core Units
Some remarks:
Program structures and units are subject to change through the process of regular course revision. There is no guarantee that every unit will be offered in any particular trimester.
*Additional Fee
It is mandatory for the awarding of the Master of Data Analytics degree that the student undertakes the final year project units: MDA691 Project Management and Research Methods, and MDA692 Data Analytics Capstone Project. If a third party is required to find a project for the student, the student will incur a fee.
The MDA course is designed to encompass two streams, one for cognate and another for non-cognate students.
Cognate students are those that have an Australian Bachelor degree or equivalent in an Information and Communications Technology (ICT) discipline such as Computer Science, Computer Engineering, Information Technology and Software Engineering.
For the non-cognate stream, students must have an Australian Bachelor degree or equivalent in a non-ICT discipline. Because we have existing units that provide foundational ICT knowledge for our non-cognate students, we can accept a broader scope of students into our programs.
To qualify for entry you need to have;
The MDA course is designed to encompass two streams, one for cognate and another for non-cognate students.
Cognate students are those that have an Australian Bachelor degree or equivalent in an Information and Communications Technology (ICT) discipline such as Computer Science, Computer Engineering, Information Technology and Software Engineering.
For the non-cognate stream, students must have an Australian Bachelor degree or equivalent in a non-ICT discipline. Because we have existing units that provide foundational ICT knowledge for our non-cognate students, we can accept a broader scope of students into our programs.
For entry you need to have:
English Language Requirements
IELTS (Academic) 6.0 with no band less than 6.0 equivalent.
Students can gain credit for learning already achieved. Applicants are assessed on a case-by-case basis. Learn more about credit transfer. Read more about the process.
Applications for credit transfer must be made before or during orientation and enrollment week.
State of the art facilities
Study now and pay later with FEE-HELP.
Students studying at MIT may be eligible for FEE-HELP. FEE-HELP is a loan scheme that assists eligible fee-paying students to pay their tuition fees. An eligible person may borrow up to the FEE-HELP limit to pay tuition fees over their lifetime.
Read more about FEE-HELP or visit Study Assist.
Tuition Fees
For 2020-21 fee information visit the tuition fee page.
Youth and student allowances
For details on Youth Allowance, Austudy and ABSTUDY, visit Human Services.
Tuition Fees
For 2020-21 fee information visit the tuition fee page.
For further information please visit
Data Analytics is the process of analysing data, extracting insights and information on trends, finding answers to questions and insights. Data analysts create systems that gather relevant data, analyse the data and manage the data through collection, storage and retrieval.
Networking establishes the system and infrastructure, data analytics takes the data and information that the networks generate and turns it into a story. Data Analytics requires different skills in analysis and strategy from the data.
Data analysts take control of business data and make sense of it, so it can translate into strategies to drive a business forward.
They use the latest technology in Artificial Intelligence (AI), Data Science, Big Data Analytics, Visualisation, Smart Sensors and Cloud Computing to improve the way we do business.
According to Job Outlook, the salary for data analysts is higher than average. Salaries ranging from $75000 to $100000 + for highly skilled analysts. Skilled data analysts are in high demand, and the industry is expected to grow rapidly.
Before applying, make sure you:
You should provide certified copies of your academic and other essential documents at the time of application.
You must upload all requested documents at the time of the application.
Learn more about the whole of the institution set here.
Phone our friendly student recruitment team on 1800 648 669.
enquiries@mit.edu.au
Before applying, make sure you:
You must upload all requested documents at the time of the application.
If you are looking to apply for a credit transfer, you must submit the following supporting documents with your credit application:
You should provide certified copies of your academic and other essential documents at the time of application.
Offshore international students must apply through an MIT authorised agent in their home country.
Phone our friendly student recruitment team on 1800 648 669.
enquiries@mit.edu.au
In the final year, students consolidate their learning through a capstone project. MIT’s School of IT & Engineering has designed these units to provide you with real-world experience, working for an industry client.
The projects are supervised by academic staff and industry supervisors, providing a fully immersive work-integrated learning (WIL) experience for students.
Each project works through system specification, analysis, design, development, implementation, testing and troubleshooting.
Our school attracts some of the best minds in the fields of Engineering and Networking. Our staff are industry experts. They drive research in the field and they bring energy to the classroom.
Working in data analytics has given Paul Kwan an exciting career working all over the globe. Before MIT, Paul taught for 15 years at The University of New England (UNE) in NSW, where he was Professor and Head of Computer Science. He joined Melbourne Institute of Technology in 2020 as Program Leader and Professor of Data Analytics.
Paul has a doctoral degree in Advanced Engineering Systems from The University of Tsukuba (Japan) majoring in Intelligent Interaction Technologies. His Bachelor and Master degrees were in Computer Science, awarded by Cornell University and University of Arizona in the USA.
He has extensive professional experience working in his native Hong Kong in ICT industries.
His areas of expertise include Artificial Intelligence, Computer Vision, Data Mining, and Machine Learning.
Paul has been a member of Australian Computer Society (ACS) since 2006, Senior Member of Association of Computing Machinery (ACM) since 2008, and Senior Member of IEEE, the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity, since 2010.
Professor Agbinya is the author of a number of textbooks on networks and wireless communication. There’s no better person to learn from. His research includes inductive communication systems, big data analytics, wireless power transfer and the Internet of Things. He leads the Engineering and IT Schools at MIT.
Johnson’s previous experience includes lecturing at University of Technology Sydney, and senior research roles at Vodafone Australia and CSIRO Telecommunications developing speech recognition software for mobile phones.
Professor Agbinya is the author of a number of textbooks on networks and wireless communication. There’s no better person to learn from. His research includes inductive communication systems, big data analytics, wireless power transfer and the Internet of Things. He leads the Engineering and IT Schools at MIT.
Working in data analytics has given Paul Kwan an exciting career working all over the globe. Before MIT, Paul taught for 15 years at The University of New England (UNE) in NSW, where he was Professor and Head of Computer Science. He joined Melbourne Institute of Technology in 2020 as Program Leader and Professor of Data Analytics.
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When you study a Master of Data Analytics, you’ll make friends and industry connections that last a lifetime. Our welcoming student support team will help you start your career on the right foot and stay in touch as your career progresses. Our alumni network is active and encouraging.
At MIT you’re more than a number. Our teachers know students by name. And our teaching methods support and challenge you to reach your potential.
Our care goes beyond the classroom. We ensure students have the support and skills they need to succeed in life and study.
We understand that choosing a course can be daunting at times. Our friendly student support service is there to answer your questions.
At MIT you’ll experience great teaching in a supportive environment. And you’ll graduate with the skills you need to succeed.
Call our friendly student services team today to discuss your learning journey on +61 3 8600 6700.