Master of Science in Information Technology (Information Technology Management)

Master of Science in Information Technology
(Information Technology Management)

This programme is designed for graduates from an IT-related discipline. It is a professional qualification designed to provide you with practical understanding and knowledge for managing IT use, change and development. You will learn new applied skills in the areas of knowledge management, data communications and business analysis. You will also increase your knowledge of IT and benefit from an emphasis on professional practice, effective communication and project management using technical and non-technical means.

The Murdoch Advantage

Complete in 24 months
Plan your own schedule & study at your own pace

MIT Units

  • Applied Information Security Management
  • Business Analysis and Systems Development Approaches
  • Business Analytics
  • Data Resources Management
  • Information Technology Project Management
  • Information Technology Research Methods
  • Information Technology Strategy
  • IT Professional Practice
  • Knowledge Management

Elective Units (Select 1 to 2 units)

  • Artificial Intelligence
  • Data Analytics
  • Foundations of Data Science
  • Human Factors in Information Technology
  • Human Resource Management Perspectives
  • International Business Negotiations
  • IT Group Project
  • Leading the Engaged Enterprise
  • Managing, Evaluating and Developing Human Resources
  • Organisational Behaviour and Management
  • Quantitative Research for Business
  • Strategic Marketing Management
  • Strategies for Growth and Excellence

The elective will be determined by Murdoch University, depending on the applicant’s academic background.
The units offered may vary depending on the applicant’s academic backgrounds.


  • Track the behaviour of applications used within a business and how they interact with each other and with users. Application Architects are focused on designing the architecture of applications, including building components like user interface and infrastructure.

  • Business Intelligence (BI) Developers design and develop strategies to assist business users in quickly finding the information they need to make better business decisions. Extremely data savvy, they use BI tools or develop custom BI analytic applications to facilitate the end users’ understanding of their systems.

  • Transform and manipulate large data sets to suit the analytical outcome for companies. For many companies, this role can also include tracking web analytics and analysing A/B testing. Data Analysts also aid in the decision-making process by preparing reports for organisational leaders who effectively communicate trends and insights gleaned from their analysis.

  • Ensure data solutions are built for performance and design analytics applications for multiple platforms. In addition to creating new database systems, Data Architects often find ways to improve the performance and functionality of existing systems, as well as working to provide access to Database Administrators and Analysts.

  • Perform batch processing or real-time processing on gathered and stored data. Data Engineers are also responsible for building and maintaining data pipelines which create a robust and interconnected data ecosystem within an organisation, making information accessible for Data Scientists.

  • Find, clean and organise data for companies. Data Scientists will need to be able to analyse large amounts of complex raw and processed information to find patterns that will benefit an organisation and help drive strategic business decisions.

  • An Enterprise Architect is responsible for aligning an organisation’s strategy with the technology needed to execute its objectives. To do so, they must have a complete understanding of the business and its technological needs to design the systems architecture required to meet those needs.

  • Oversee that all business systems are working optimally and can support the development of new technologies and system requirements. A similar job title is the Cloud Infrastructure Architect, who oversees a company’s cloud computing strategy.

  • Machine Learning Engineers create data funnels and deliver software solutions. They typically need reliable statistics and programming skills as well as a knowledge of software engineering. In addition to designing and building machine learning systems, they are also responsible for running tests and experiments to monitor such systems' performance and functionality.

  • Research new data approaches and algorithms to be used in adaptive systems, including supervised, unsupervised and deep learning techniques.

  • Statisticians work to collect, analyse and interpret data to identify trends and relationships which can inform organisational decision making. Additionally, their daily responsibilities include designing data collection processes, communicating findings to stakeholders and advising corporate strategy.


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