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Study masters degree business & management online with Swinburne University of Technology through Open Universities Australia. Explore all degrees, subjects and short courses now.

Professional development that really countsEquip yourself with the skills needed to thrive in your industry and achieve your unique career goals. Our Master of Business Administration (MBA) is all about growth. Scale up your skillset and your earning potential as you are expertly guided through the key steps to exponential growth: strategy, innovation, marketing and management. Harness your entrepreneurial drive with cutting-edge business insight that will allow you to make crucial business decisions with confidence and lead teams to success.There’s no need to put your career on hold while you study. Our MBA is 100 per cent online, making it the most convenient way to gain an industry-recognised, AACSB accredited master’s degree. Plan your learning around your existing work, family and personal commitments, and study on your terms.Why Swinburne Online<ul><li>Tailor your master’s: Gain a well-rounded overview of all aspects of business by selecting business electives, or gain expert knowledge in the Project Management or Cybersecurity Management specialist streams.</li><li>Award winning, top-tier MBA: Receive exactly the same globally recognised master’s qualification as Swinburne’s on-campus students. Swinburne University’s MBA has a Tier-1 rating and is in the top Online MBAs in CEO Magazine’s 2022 Global Rankings.</li><li>Multiple entry and exit points: Choose to complete your MBA in as little as 16 months, or tackle your course in bite-sized chunks of four units: graduate certificate (four units), graduate diploma (eight units), then master’s (12 units).</li></ul>

Become an innovative leader. You’ll study core business subjects including marketing, accounting, and economics. Delve deeper into business or choose the project management stream. Build executive skills and get strategic about your business future.

Master of Business Administration

Research Design

Business Analytics and Artificial Intelligence

Agile Methods for Business Analysis

IT Program and Project Management

Sustainable Business Practice

Basic Statistical Computing Using R

Statistical Practice 1

This unit aims to develop and enhance students&#39; conceptual and practical understanding of data analytics and artificial intelligence in the contemporary business context. Students will have an opportunity to immerse themselves in problem-solving activities requiring lateral and critical thinking by exploring structured and unstructured data, considering and applying the appropriate analytic and artificial intelligence techniques using a software programming environment for statistical computing (such as R) and visualisation tools and approaching organisational problems through data-driven decision-making processes. Further, students will learn fundamental concepts, key techniques and popular tools in artificial intelligence and how it is applied in business and industry.

Learn how to use AI to unlock data for business success. You’ll build on your programming knowledge as you explore statistical computing and visualisation tools. Use machine learning to problem solve and develop business solutions. 

This unit provides students the opportunity to explore various approaches to planning and managing information technology programs and projects. Students will consider issues relating to the development and implementation of technology based on various lifecycle models, frameworks and agile and waterfall methodologies. The main emphasis will relate to the use of agile and waterfall methods, tools, techniques, and processes for planning and managing IT programs and projects. This unit will also expand upon PMBoK [Project Management Body of Knowledge] concepts, scrum concepts and integrate several recent developments in relation to understanding the human side of IT project management, such as stakeholder analysis and human resources management.

This subject teaches students to identify some of the methodologies used in survey research. It includes an overview of the procedures used in survey research, a descriptive approach to methods including questionnaire design, data collection, and an introduction to survey sampling. It covers ethics and laws in conducting research. It also covers topics related to incidence and prevalence, standardisation, different types of study designs including cohort and case-control studies, randomised control trials and clinical trials in health statistics and elsewhere. Case studies will be drawn from areas such as sociology, market research, psychology, medical sciences and other areas as appropriate.

Survey research methods and get critical about design. Describe approaches and observe techniques. Sample data collection methods. Scale and graph procedures and figure out incidence and prevalence. Draw on case studies and assess and present data

This subject was previously known as Business Intelligence.
This subject covers issues relating to deriving intelligence from various data sources for decision making purposes. Students gather skills to drive improved decision making process for senior management based on understanding data. Students will know the importance of understanding the short and long term goals of the organisation and how these impact the decision making process. Student will use tools that enable data analysis, predictive analytics, data visualisation to assist in the delivery of delivering real-time actionable intelligence.

Get data smart. Source intelligence from diverse data supplies to help senior management make decisions that solve major commercial problems. Use analysis, predictive analytics, and data visualisation tools to generate key data insights. 

Business Intelligence and Data Visualisation

This subject introduces R, one of the popular open source statistical programming languages commonly used in applied statistics and data science disciplines. Students will learn key programming principles of R and develop competence in programming in R which are essential for a statistician or data scientist to perform different types of statistical analyses.This subject was formerly known as STA60003 Basic Statistical Computing

Upskill and package up your computer and statistical knowledge. Form questions. Use SPSS software to select, modify, merge and apply data visualisation techniques. Investigate missing values and manage complex data files. 

This subject develops students’ understanding of a range of statistical methods along with their assumptions and limitations of their application. It enables students to develop the capacity to carry out independent statistical analysis of data using a standard statistical software package and also aims to develop students’ abilities in effectively communicating the outcomes of statistical investigations. In addition, it will provide a foundation and motivation for exposure to statistical ideas subsequent to the Graduate Certificate (GC) degree.

Develop a number of statistical data techniques; assess theories and survey limitations. Increase analysis skills and translate investigation outcomes. Recognise statistical inference and sampling distributions. Transcribe interpretative summaries. 

This subject will introduce students to fundamental statistical areas of research design and linear models. It examines how multiple regression and Analysis of Variance (ANOVA) can be used to analyse experimental and observational research using a variety of research designs.
As the subject builds on the skills developed in STA10003 Foundations of Statistics, this prerequisite is strictly enforced.

Line up and calculate statistical modelling for a range of research designs. Examine how analysis of variance (ANOVA) and multiple regression methods are used to assess experimental and observational research data. Interpret results and write reports.

Analysis of Variance and Regression

This unit enables students to stand out as effective business analysts in agile software development and implementation teams. Students learn how to apply agile methods and problem-solving tools and techniques that assist in the analysis of complex, socio-technical problems which typify the nature of organisational information systems, and the work of business and information analysts. Drawing on real-world cases, the unit encompasses the technical, social and human dimensions of information systems problem solving. The value of uncovering multiple perspectives and multiple objectives, that are likely to exist in complex problem situations and which could impact agile information systems projects, is also analysed.

This unit aims for students to use a range of models and frameworks to facilitate a comprehensive understanding of the challenges and opportunities facing today’s business. Through this holistic application students will analyse and evaluate business problems in order to offer practical, innovative and creative solutions which display awareness of the impact of such decisions on the organisation’s triple bottom line, that is, people, planet and profit. Advanced Innovative Business Practice is the first of the two mandatory capstone units of the Bachelor of Business.

This subject extends the ideas developed in Statistical Practice 1 to include more advanced analyses, broaden the range of applications students are familiar with so that they will be able to carry out independent statistical investigations, and develop an awareness of the assumptions and limitations involved in the generalisation of results of such investigations.

Practice and advance your statistical knowledge and extend ideas. Produce an independent investigation. Get analytical and compare groups using parametric and non-parametric methods. Stop generalising, question assumptions and identify data limits. 

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