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2 years full-time
Face-to-face
Level 3 & 4, 545 Kent Street, Sydney NSW 2000, Australia
Full-time · 2 sessions of 4 hours each per week (standard units); 2 sessions of 6 hours each per week for 3 weeks plus 1 assessment week (intensive units); approximately 7–9 hours per week self-directed study per unit
February | March | May | June | August | September | October | November | 2026 Semester 1 Block 4 (Start of Classes: 1 Jun 2026)
Course Overview
Eligibility
Tuition fee
Course tuition fee over 2 years: $44,000 (2024) / $46,240 (2026). Fee per annum: $22,000 (2024) / $23,120 (2026). Fee per unit: $2,750 (2024) / $2,890 (2026). All fees in Australian dollars. Fees are subject to change without notice. Course fees are to be paid in full before enrolment/selection of subjects in any given semester.
Duration
2 years full time
Intakes
February | March | May | June | August | September | October | November
Study mode
On-campus / Full-time
Career & Study Pathways
Course Content
Information Systems Applications in Business
Introduces the most relevant concepts used to manage the integration of information systems (IS) into business and society. Covers simplifying the use of technology in complex IS business environments, and builds students' awareness of the relationship between IS functionality and business process requirements, including how organisations use IS to process data into information for critical decision-making.
Database Management Systems
Introduces students to the fundamentals of relational databases, data modelling using entity relationship diagrams, structured query language (SQL), procedural language (PL), data analysis, sharing options, database security, distributed database management systems, and data mining.
Software Development
Covers the fundamentals of software development including investigating client application software problems, evaluating approaches, and designing solutions using a programming language such as Python. Takes students through the full software development lifecycle including writing specifications, testing and design.
Systems Analysis Design
Covers principles of analysis and design for information systems, including data requirements gathering, data modelling at conceptual/logical/physical levels, functional dependencies, domain normalisation, and user-centred design approaches.
Big Data and Visualisation
Introduces concepts of big data analytics and visualisation, business motivations and drivers for big data adaptation, enterprise technologies, big data business intelligence, algorithms and machine learning techniques for big data, and data visualisation tools and techniques. Pre-requisite: MBIS4002 & MBIS4003.
Business Process Management
Facilitates examination and improvement of business operations using conceptual frameworks and business process modelling software tools to solve complex business problems and improve organisational effectiveness. Pre-requisite: MBIS4004 (Co-requisite).
Professional Practice in Information Systems
Educates students about ethical, legal and social issues faced by IS professionals, including data and privacy, confidentiality, cybercrime and internet fraud, and develops negotiation and conflict resolution skills.
Discovering Data Analytics
Develops conceptual understanding of data analytics in real-world applications, covering the lifecycle of a data science project (data collection, management, wrangling, analytics and visualisation), privacy/ethical issues, and preparation for the Google Data Analytics Professional Certificate. Pre-requisite: MBIS4002 & MBIS4003.
Business Analytics
Introduces concepts and techniques for leveraging organisational data for strategy and decision-making, including regression, time series, classification, clustering, and natural language processing. Uses Python, associated libraries, and KNIME. Pre-requisite: MBIS4007.
Applied Data Analytics
Introduces techniques for extracting meaningful information from real-world datasets, covering probability and statistics, generalised linear models, classification, advanced regression, unsupervised statistical learning, and statistical programming in Python or R. Pre-requisites: MBIS4003 & MBIS4016.
Data Analyst Professional
Covers the role of a Data Analyst including technical skills, ethical/privacy/governance considerations for managing data, data security techniques, and effective communication with business units and management.
Project Management for Data Analytics Solutions
Develops skills in designing effective and viable data science solutions using project management and system analysis techniques specific to data science, including UML analysis and design, data science project requirements, and design patterns. Pre-requisites: MBIS4004, MBIS4016 & MBIS5009.
Cloud and Big Data for Data Analytics (Elective)
Covers cloud computing technologies and their use in business for big data analytics, including cloud architectures, parallel database systems, map/reduce, key-value stores, virtualisation, multi-tenant databases, association analysis, classification and prediction, and cluster analysis. Pre-requisites: MBIS4003 & MBIS4016.
Machine Learning for Data Analytics (Elective)
Enables deep understanding of design and implementation of analytics solutions using machine learning algorithms, including parametric and non-parametric models, learning techniques, and ethical principles in machine learning. Pre-requisites: MBIS4003 & MBIS5009.
Systems Security Professional (Elective)
Introduces the profession of a security officer in a business information systems environment, covering eight domains of the Common Body of Knowledge (CyBOK) and preparation for the CISSP industry certification exam from ISC2.
Artificial Intelligence Fundamentals (Elective)
Introduces fundamental concepts and application fields of AI including knowledge representation, searching, reasoning, expert system design, intelligent agents, and responsible AI principles. Pre-requisites: MBIS4003, MBIS4016 & MBIS5009.
Business Analytics and Intelligence (Elective)
Equips students with knowledge and skills in Business Intelligence (BI) and Data Mining (DM), covering statistical modelling, visualisation techniques, descriptive/predictive/prescriptive analytics, and use of KNIME. Pre-requisites: MBIS4008 & MBIS5009.
Practical Industry Projects - PIP (Part A)
Capstone project in partnership with Practera integrating classroom knowledge into practical experience solving real-world business challenges for industry clients. Students work in groups of up to six, guided by a client mentor and lecturer. Pre-requisite: completion of 110 course credit points.
Practical Industry Projects - PIP (Part B)
Continuation of the Practical Industry Projects Capstone. Pre-requisite: MBIS5015a.
Common Questions
The total course tuition fee over 2 years is $44,000 (2024 fees) or $46,240 (2026 fees). The fee per annum is $22,000 (2024) or $23,120 (2026), and the fee per unit is $2,750 (2024) or $2,890 (2026). All fees are in Australian dollars, are subject to change without notice, and must be paid in full before enrolment/selection of subjects in any given semester.
The course consists of 15 units totalling 160 credit points, including a Capstone Project worth 20 credit points. There are 13 compulsory units and 2 elective units. Students can exit early with a Graduate Certificate of Business Information Systems (Data Analytics) after successfully completing 4 units (6 months full-time), or with a Graduate Diploma of Business Information Systems (Data Analytics) after successfully completing 8 units (1 year full-time).
The course has multiple intakes throughout the year: February, March, May, June, August, September, October, and November. For 2026 Semester 1 Block 4, classes start on 1 June 2026, with a census date of 8 June 2026.
Students must complete 2 elective units from the following options: MBIS5008 Cloud and Big Data for Data Analytics, MBIS5023 Machine Learning for Data Analytics, MBIS5021 Systems Security Professional, MBIS5017 Artificial Intelligence Fundamentals, and MBIS5018 Business Analytics and Intelligence. Each elective has specific pre-requisites.
The course is delivered face-to-face at the Sydney or Melbourne campus. Standard units run in a 4-week block model with 2 sessions of 4 hours each per week. Intensive units run 2 sessions of 6 hours per week for 3 weeks, with the 4th week for assessment submission. In addition, students should set aside approximately 7–9 hours per week per unit for self-directed study including assignments, readings, projects, and workshop preparation.
Several units align with industry certifications: MBIS4016 assists preparation for the Google Data Analytics Professional Certificate; MBIS5001 can be considered for the Specialist Data Scientist professional certificate (DASCA); MBIS5003 can be considered for the Certified Analytics Professional program; MBIS5008 can be considered for the Cloud Computing Certification Program; MBIS5017 and MBIS5023 together can be considered for the Artificial Intelligence Board of America (AiE) certification; MBIS5018 assists preparation for the Certified Business Intelligence Professional certification; and MBIS5021 helps prepare for the CISSP exam from ISC2.
Application
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