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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 a 4th week for assessment submission (intensive units); approximately 7–9 hours per week additional self-study per unit
February | March | May | June | August | September | October | November | 2026 Semester 1 Block 4 (Jun 1, 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
Entry requirements
Career & Study Pathways
Course Content
Information Systems Applications in Business
Introduces information systems (IS) concepts for managing integration of IS into business and society. Covers the relationship between IS functionality and business process requirements, and how organisations use IS to process data for competitive advantage decision-making.
Database Management Systems
Introduces fundamentals of relational databases including data modelling, entity relationship diagrams, SQL, procedural language (PL), data analysis, database security, distributed database management systems, and data mining.
Software Development
Covers fundamentals of software development including investigation of client application problems, solution design using Python, software development lifecycle, writing specifications, testing and design, and core programming principles.
Systems Analysis Design
Covers principles of analysis and design for information systems, including data requirements gathering, conceptual/logical/physical data modelling, functional dependencies, domain normalisation, and user-centred design.
Big Data and Visualisation
Introduces big data analytics and visualisation concepts, enterprise technologies, big data business intelligence, algorithms and machine learning techniques for big data, and data visualisation tools and techniques including dashboards. Pre-requisite: MBIS4002 & MBIS4003.
Business Process Management
Examines and improves business operations using business process modelling software tools, conceptual frameworks, and analysis/design of business processes. Pre-requisite: MBIS4004 (Co-requisite).
Professional Practice in Information Systems
Covers ethical, legal and social issues for IS professionals including data and privacy, confidentiality, cybercrime and internet fraud, professional codes of ethics, and negotiation and conflict resolution.
Discovering Data Analytics
Develops conceptual understanding of data analytics in real-world applications including data collection, management, wrangling, analytics and visualisation, privacy, security and ethical issues, and preparation for the Google Data Analytics Professional Certificate. Pre-requisite: MBIS4002 Software Development & MBIS4003 Database Management System.
Business Analytics
Introduces concepts and techniques for leveraging organisational data including regression, time series, classification, clustering, natural language processing, and use of Python, associated libraries, and KNIME. Pre-requisite: MBIS4007.
Applied Data Analytics
Introduces techniques for extracting meaningful information from real-world datasets including probability, statistics, generalised linear models, classification, advanced regression, unsupervised statistical learning, and statistical programming using Python or R. Pre-requisites: MBIS4003 Software Development & MBIS4016 Discovering Data Analytics.
Data Analyst Professional
Covers the Data Analyst profession including ethical, privacy and governance considerations for managing data, data security, communication with business units and management, and understanding business needs.
Project Management for Data Analytics Solutions
Develops skills in designing data science solutions using project management and system analysis techniques, UML analysis and design diagrams, requirements analysis, and design patterns. Preparation for Certified Analytics Professional program. Pre-requisites: MBIS4004, MBIS4016 & MBIS5009.
Cloud and Big Data for Data Analytics (Elective)
Studies cloud computing technologies for big data including cloud architectures, parallel database systems, map and reduce, key-value stores, virtualisation, multi-tenant database systems, association analysis, classification, cluster analysis, and mining complex data types. Pre-requisites: MBIS4003 & MBIS4016.
Machine Learning for Data Analytics (Elective)
Covers design and implementation of analytics solutions using machine learning algorithms, parametric and non-parametric models, ethical principles in machine learning, and state-of-art methods and tools for deploying machine learning models. Pre-requisites: MBIS4003 & MBIS5009.
Systems Security Professional (Elective)
Introduces the profession of security officer in a business information systems environment, covering eight domains of Common Body of Knowledge (CyBOK) and preparation for the CISSP industry certification exam from ISC2.
Artificial Intelligence Fundamentals (Elective)
Introduces fundamental AI concepts including knowledge representation, searching, reasoning, expert system design, intelligent agents, responsible AI principles, and design/development of AI models for real-world problems. Pre-requisites: MBIS4003, MBIS4016 & MBIS5009.
Business Analytics and Intelligence (Elective)
Equips students with knowledge in Business Intelligence (BI) and Data Mining (DM) including data types, statistical modelling, visualisation, BI applications, text and web mining, descriptive/predictive/prescriptive analytics, and KNIME. Preparation for Certified Business Intelligence Professional certification. 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, in groups of up to six with client mentor and lecturer guidance. Students receive certification and a digital badge. 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 for 2024 and $46,240 for 2026. 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 and are subject to change without notice. Course fees are to be paid in full before enrolment/selection of subjects in any given semester.
The course comprises 15 units totalling 160 credit points, including a Capstone Project worth 20 credit points. There are 13 compulsory units and 2 elective units. Students may exit early with a Graduate Certificate of Business Information Systems after successfully completing 4 units (approximately 6 months full-time), or with a Graduate Diploma of Business Information Systems (Data Analytics) after completing 8 units (approximately 1 year full-time). The full Master award requires completion of all 15 units.
The course has multiple intakes throughout the year: February, March, May, June, August, September, October, and November. Additionally, a 2026 Semester 1 Block 4 intake has classes starting 1 June 2026, with the last date to enrol also being 1 June 2026 and a census date of 8 June 2026.
Graduates can pursue roles such as Data Analyst, Data Scientist, Data Architect, Business Analyst, Data Analytics Consultant, Data Mining Analyst, and Data Visualisation Analyst. Completion of the Master also meets the academic requirement for admission to Doctorate courses within Australia and overseas, subject to additional institution and course-specific requirements.
The course is delivered face-to-face at AIH's Sydney campus (Level 3 & 4, 545 Kent Street, NSW 2000) and Melbourne campus (Level 1, 20 Queen Street, VIC 3000). Standard units are delivered in a 4-week block model with 2 sessions of 4 hours each per week. Intensive units involve 2 sessions of 6 hours per week for 3 weeks, with the 4th week for assessment submission. Students should also set aside approximately 7–9 hours per week per unit for self-study, assignments, readings, and projects.
Students must complete 2 elective units chosen 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, so students should review those requirements before selecting.
Application
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Step 03
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Master of Nursing · Griffith University
