This unit is used by the faculty to enrol students undertaking outbound exchange studies at a host institution. Students will not be able to enrol in this unit via WES. The faculty will manage the enrolment of students undertaking an outbound exchange program to ensure fees and credit are processed accurately.

This unit is used by the faculty to enrol students undertaking outbound exchange studies at a host institution. Students will not be able to enrol in this unit via WES. The faculty will manage the enrolment of students undertaking an outbound exchange program to ensure fees and credit are processed accurately.

This unit is used by the faculty to enrol students undertaking outbound exchange studies at a host institution. Students will not be able to enrol in this unit via WES. The faculty will manage the enrolment of students undertaking an outbound exchange program to ensure fees and credit are processed accurately.

This unit is used by the faculty to enrol students undertaking outbound exchange studies at a host institution. Students will not be able to enrol in this unit via WES. The faculty will manage the enrolment of students undertaking an outbound exchange program to ensure fees and credit are processed accurately.

This unit is used by the faculty to enrol students undertaking outbound exchange studies at a host institution. Students will not be able to enrol in this unit via WES. The faculty will manage the enrolment of students undertaking an outbound exchange program to ensure fees and credit are processed accurately.

This unit is used by the faculty to enrol students undertaking outbound exchange studies at a host institution. Students will not be able to enrol in this unit via WES. The faculty will manage the enrolment of students undertaking an outbound exchange program to ensure fees and credit are processed accurately.

This unit is used by the faculty to enrol students undertaking outbound exchange studies at a host institution. Students will not be able to enrol in this unit via WES. The faculty will manage the enrolment of students undertaking an outbound exchange program to ensure fees and credit are processed accurately.

This unit is used by the faculty to enrol students undertaking outbound exchange studies at a host institution. Students will not be able to enrol in this unit via WES. The faculty will manage the enrolment of students undertaking an outbound exchange program to ensure fees and credit are processed accurately.

This unit is used by the faculty and/or the Monash Institute of Graduate Research to enrol students undertaking Higher Degrees by research. Students will not be able to enrol in this unit via WES.

This unit exposes students to research across the range of IT disciplines, preparing them to conduct research in their home discipline. It provides broad coverage of the issues, concepts, methods and techniques associated with Computer Science, Software Engineering, Information Systems and Information Management. It introduces students to major research philosophies and paradigms, the principles of research design, research ethics, and research methods and techniques of data collection and analysis appropriate to IT research generally and to their sub-discipline specifically. It covers oral and written communication skills.

Skills developed and knowledge acquired from this unit will prepare students to conduct and communicate their own research, as well as to be knowledgeable and critical interpreters of others' research.

On completion of this unit, students should be able to:

1. review and critique research literature, research design and reported findings in a sub-discipline of IT;
2. communicate research findings, orally and in writing, in research and industry settings;
3. explain the ethical and professional issues that may arise in IT research and demonstrate them in practice;
4. identify, explain and critique major research philosophies and paradigms;
5. evaluate, select and justify research methods and techniques of data collection and analysis appropriate to particular research designs, projects and disciplines;
6. analyse and describe the technical, professional and socio-economic contexts that motivate research, and the implications of research outcomes;
7. design and carry out a rigorous and ethical research project and produce a report explaining the project, its design and interpretation of the results.
8. apply research skills to operate effectively as a member of a research project team.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two 2-hour workshops
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit will develop students capabilities to undertake research in the information systems field. Students will learn various research methods and study published research papers in which these research methods have been used. In particular, students will learn to evaluate how well the research methods have been used in published research papers. Students will also develop an understanding of some of the exciting, leading-edge research in the information systems field. This understanding may enable students to identify research topics that they would like to pursue, perhaps in an honours, masters, or PhD thesis.

At the completion of this unit, students should be able to:

1. undertake research in the information systems field;
2. explain various research methods used in the information systems field;
3. evaluate how well research methods have been used in published research papers.

Examination (2 hours): 40%; In-semester assessment: 60%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • One 3-hour seminar
2. Additional requirements (all students):
   • A minimum of 9 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Methods from Artificial Intelligence (AI) form the basis for many advanced information systems. These techniques address problems that are difficult to solve or not efficiently solvable with conventional techniques. Building on the undergraduate curriculum this unit introduces the student to advanced AI methods and their applications in information systems.

On completion of this unit students, should be able to:

1. describe an overview of different technologies that form the basis of intelligent information systems;
2. explain the capabilities of these methods;
3. recognise tasks that can be solved with these methods;
4. judge the limitations of these methods;
5. apply several standard techniques in the chosen sub-fields of intelligent information systems to the construction and design of such systems;
6. critically evaluate the performance of these approaches;
7. compare these techniques to alternative approaches;
8. explain the practical relevance of intelligent information systems.

Assignment and Examination, relative weight depending on topic composition. When no exam is given students will be expected to demonstrate their knowledge by solving practical problems and maybe required to give an oral report.

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
2. Additional requirements (all students):
   • A minimum of 10 hours independent study per week for completing assignment and project work, private study and revision.

See also Unit timetable information

Algorithms are the most fundamental area for all aspects of computer science and software engineering. Discrete structures, such as those treated in graph theory, set theory, combinatorics and symbolic logic form the mathematical underpinning of the study of algorithms. As well-designed algorithms and data structures are essential for the good performance of an information system, an in-depth understanding of the theoretical properties of algorithms is essential for any computer scientist. As importantly, the theoretical investigation of algorithms leads to a deeper understanding of problem structures and classes of problems and the knowledge of a large variety of algorithm types enables the designer to approach a new problem from different angles. Topics for this unit may include: Computability and Complexity, Automata Theory, Advanced Analysis and Design of Algorithms, Parallel and Distributed Algorithms, Numerical Algorithms, Cryptographic Algorithms, Spatial/geometric Algorithms, Approximation Algorithms and Randomised Algorithms.

On successful completion of this unit, students should be able to:

1. critically analyse and assess algorithms for use in the chosen specialisation area;
2. be able to formally analyse algorithms in this specialisation area;
3. choose and apply algorithms and data structures in the specialisation area;
4. design and implement modified algorithms in the chosen area to suit particular problem structures.

Assignment and Examination, relative weight depending on topic composition. When no exam is given students will be expected to demonstrate their knowledge by solving practical problems and maybe required to give an oral report.

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory or tutorial
2. Additional requirements (all students):
   • A minimum of 2-3 hours of personal study per one hour of contact time in order to satisfy the reading and assignment expectations.

See also Unit timetable information

All sciences are increasingly relying on computational support and the growth of many branches of science has only become possible due to the availability of efficient computational methods. The common basis of such methods are; numerical methods and high performance computing. Topics for this unit include: Numerical Methods, High Performance and Parallel Computing, Optimisation and Operations Research Bioinformatics, Simulation, Visualisation and Modelling.

At the completion of this unit students should be able to:

1. explain the role of computational methods in the chosen field of specialisation and their relation to complimentary and related approaches;
2. solve non-trivial problems using the algorithms specific to the chosen field of specialisation;
3. compare and evaluate alternative computational approaches in the chosen domain in terms of performance and suitability to a specific problem;
4. critically evaluate the limits and capabilities of these methods;
5. select, design and test computer programs in the domain;
6. use standard computational packages in the chosen domain effectively for practical problem solving where appropriate.

Assignment and Examination, relative weight depending on topic composition. When no exam is given students will be expected to demonstrate their knowledge by solving practical problems and maybe required to give an oral report.

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
2. Additional requirements (all students):
   • A minimum of 10 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit focuses on the design, construction and deployment of mobile applications, with particular focus on Android and iOS platforms. Areas such as mobile data management and networking, MVC design patterns, and mobile GUI design considerations will be explored. The unit will emphasise hands-on, practical experience with actual devices and emulators. Research topics and ideas will also be covered for post-graduate students.

At the completion of this unit, students will:

1. recall the history of mobile platforms and the development of software for those platforms;
2. describe the MVC design pattern and explain the importance of this design pattern in mobile applications development;
3. critically analyse and distinguish between the design considerations for mobile application interface development and traditional interfaces;
4. analyse and implement the use of graphic and audio components in the development of mobile applications;
5. investigate, design, construct and publish applications for mobile platforms with particular focus on Android and iOS.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

FIT5000 is an extension unit for all FIT coursework masters minor thesis degrees, where appropriate. Entry only available on approval by the Associate Dean (Education) where exceptional circumstances have been determined.

On completion of the Masters thesis, students will be able to:

1. design a rigorous Masters level research project and develop project proposal;
2. critically review research literature, research design and reported findings;
3. evaluate and select research methods and techniques of data collection and analysis appropriate to particular research designs, projects and disciplines;
4. conduct ethical research;
5. communicate research findings in written and oral form in research and industry settings.

Presentation and final thesis (normally 15,000 - 20,000 words): 100%

Varies according to remaining requirements. To be determined by the Supervisor/Co-ordinator.

See also Unit timetable information

This unit aims to introduce the secure software development issues including secure software development life cycle, secure software design principles, secure coding practices, threat evaluation models, secure software testing, deployment and maintenance, software development and security policy integration. Students are provided with a range of practical exercises and tasks to reinforce their skills including: identification of security bugs in programs written in different programming languages, design, implementation, and testing of secure concurrent and networked applications, identification of vulnerabilities in networked and mobile/wireless applications. In addition, students will learn input validation techniques to minimise security risks, man-in-the-middle attack techniques to be able to build more secure networked applications, practical secure software testing techniques to be able to test applications for security bugs.

On successful completion of this unit, students should be able to:

1. investigate methods that are appropriate for the realisation software security;
2. investigate and model the possible vulnerabilities and threats for a given application system;
3. design, implement and produce test procedures and perform evaluation of software security features of concurrent and networked applications.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Networks and security

In-depth coverage of the protocols used to operate the Internet and intranets, and a selection of major applications, including specific implementations of the protocols and systems. The topics include: Advanced Internet Addressing: IPv6, subnetting, supernetting. TCP Performance and Enhancements: Reno, New-Reno, Fast Retransmit and Recovery, etc. Unicast and multicast routing protocols: BGP4, OSPF, MOSPF, DVMRP, etc. Messaging systems: SMTP, MIME, POP3, IMAP, World Wide Web systems: client-server implementations, HTTP, Real Time Protocols: RTP, RTCP, RSVP. Security and Firewall. Quality of Service issues: DiffServ and IntServ. Network management and Remote File activities.

On successful completion of this unit, students should be able to:

1. identify the appropriate Internet protocols for a given application development;
2. design client-server applications using the TCP/IP protocols;
3. configure and performance tuning of Internet communications;
4. investigate and analyse the current technology, systems and software relevant to networks in an organisataion;
5. setup corporate networks and manage their network services; and
6. upgrade and install new network services.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Networks and security

This unit will cover network design, performance modelling and analysis. Queuing models (M/M/1, M/M/k, M/M/k/k, M/G/1), networks of queues. Multi-access systems (splitting, reservation, carrier sensing), routing techniques (shortest path, Bellman-Ford, Dijkstra, adaptive routing, flooding). Quality of service (QoS) aspects, flow control, connection admission control and other traffic management functions - ATM, IntServ and DiffServ models. Network topology design and performance modelling, design considerations for local or wide area networks, including GEPON, cable and wireless networks. Introductory probability and graph theory.

At the completion of this unit, students should be able to:

1. explain and construct queuing models for performance modelling of networks;
2. explain multi-access systems including splitting, reservation, and carrier sensing;
3. explain analysis of routing protocols commonly used on the Internet;
4. explain and apply traffic dimensioning for circuit and packet switched networks, including VoIP and multimedia;
5. explain and apply design considerations for local or wide area networks, including GEPON, cable and wireless networks;
6. explain the analysis and evaluation of the operation of a local or wide area telecommunications network.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Networks and security

This unit provides students with the knowledge, understanding and skills required to develop an application system which uses a web interface to a back-end database. The unit assumes a sound basic knowledge of programming and database concepts and skills as developed in the introductory units in these areas. The emphasis in the unit is on mastery of the key concepts and the basic knowledge and skills required to build this kind of application. The unit will provide students with an awareness of the wide range of technologies which are used to support this kind of application, but will examine only a limited number of these technologies to demonstrate the key concepts and their application.

The unit will take a strongly practical focus in examining the technology issues involved, and highlight the key issues which a developer needs to address in developing applications of this kind for real-world systems.

At the completion of this unit, students should be able to:

1. demonstrate the impact of the history of web applications development on current web-technology;
2. design, construct and publish web-database applications;
3. analyse and critique the key technological issues confronting developers building web-database applications;
4. test the key features of programming languages which are commonly used for developing web-database application;
5. assess the MVC design pattern and construct a web-database application using the MVC design pattern;
6. apply, analyse and critique a professional approach towards the development of web-database applications.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours and 10 minutes): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Enterprise networks consists of several highly complex devices that interconnect in likewise complex configurations and modes of operation. While todays network technology has come a long way in terms of high-speed data transmission, secure management components, and software-driven administration, QoS targets have come to the fore as converged technologies have taken over both enterprise and home users of network technologies. This unit will provide students with fundamentals and theoretical foundations of Quality of Service and management aspects of modern network infrastructures. On the basis of industry best practices, research- and experience-driven standardisation, this unit will cover topics pertinent to delivering quality, security, manageability and other targets that are relevant in large-scale networks. Students will also acquire practical skills needed to plan, install, configure and manage networks through laboratory activities and projects.

On successful completion of this unit, students should be able to:

1. explain key concepts of quality of service across a range of technologies, network protocols and standards;
2. describe different management techniques;
3. evaluate and use quality of service schemes and network management techniques.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination: (2 hours) 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Networks and security

Network security is an important part of any computer network and essential knowledge for IT professionals. This unit provides fundamental network security for IT students and professionals. It covers wired and wireless communication and network security, security at different layers, computer system security, network services and applications security, basic defence systems, cryptography for network security, techniques for identifying system vulnerabilities and penetration testing.

At the successful completion of this unit, students should be able to:

1. explain the fundamentals of wired and wireless network security;
2. use practical skills to identify computer system vulnerabilities and carry out penetration testing;
3. identify important network security components, then design and implement defence systems.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 30%; In-semester assessment: 70%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory/tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Networks and security

This unit provides students with an understanding of the design and development of systems that support the large enterprise in a web-based environment. Students will learn of the theoretical issues that need to be considered by the enterprise and how they can affect the development of the enterprise application. A number of techniques will be introduced as the technological means to build such an application with specific emphasis on the Java EE technology.

At the completion of this unit, students should be able to:

1. analyse and critique enterprise software architecture on the web;
2. design, construct and publish enterprise applications using the Java programming language;
3. assess various advanced Java technologies used to build web applications for the enterprise and construct enterprise applications using advanced Java technologies;
4. apply, analyse and critique the use of advanced Java libraries and frameworks in building a medium-size web application for the enterprise.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%, In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit provides a high level coverage of mobile and distributed computing. It will focus on the underlying concepts and standards of mobile computing and current technologies for mobile and distributed systems. It will discuss cellular networks, wireless networks and their standards and technologies, context-aware computing, location-awareness, wireless sensor networks, internet mobility, web services and service-oriented technology, cloud computing and current research trends and case studies.

At the completion of this unit, students will:

1. identify and describe different approaches and methods for building distributed and mobile computing systems;
2. evaluate several models and approaches and select suitable mobile computing solution to a particular case;
3. propose and develop a mobile or distributed system that is appropriate to a problem domain;
4. identify the current research directions in the field and their impacts.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit introduces the main problems and approaches to designing intelligent software systems including automated search methods, knowledge representation and reasoning, planning, reasoning under uncertainty, machine learning paradigms, and evolutionary algorithms.

At the completion of this unit, students should be able to:

1. explain the theoretical foundations of Artificial Intelligence (AI) - such as the Turing test, Rational Agency and the Frame Problem - that underpin the application to information technology and society;
2. critically explain, evaluate and apply appropriate AI theories, models and/or techniques in practice - including logical inference, heuristic search, genetic algorithms, supervised and unsupervised machine learning and Bayesian inference;
3. utilise appropriate software tools to develop AI models or software;
4. utilise and explain evaluation criteria to measure the correctness and/or suitability of models.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit focuses on a holistic approach to project management. It provides students with a high level of understanding of the processes of project management, as well as sound skills in the use of project tools. Proficiency in using key tools and concepts could give students a significant competitive advantage in the market place. The content deals with: concepts and definitions; organising and staffing the project office and team; planning, scheduling techniques; cost control; risk management; contracts and procurement; etc. Case studies, articles of interest that may appear in current media, and students' own work experiences with project management, will be discussed to optimise the learning opportunity in the unit.

On successful completion of this unit, students should be able to:

1. analyse and evaluate the role of the modern project manager in the context of IT projects;
2. interpret and critique a variety of project management methodologies offered by various professional bodies including that provided by the Project Management Body of Knowledge (PMBOK);
3. describe and apply the available strategies, techniques and decision tools used by project managers to manage modern IT projects based on PMBOK methodology.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour tutorial
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Project management

Transmission media impose various and often unique constraints on the design of networks and their achievable performance. This unit will cover key performance concepts in copper cables, optical fibre cabled and wireless transmission media. This includes atmospheric propagation impact on QoS, satellite and wireless systems, Wifi, WiMax network propagation issues and planning concepts, and satellite and terrestrial service planning concepts. The infrastructure requirements, reliability and maintainability of networks with specific transmission media will be covered, including the application of GIS, Internet of Things (IoT) and wireless sensor networks in design and planning for terrestrial, mobile and cellular systems.

On successful completion of this unit, students should be able to:

1. describe basic communications and network infrastructures;
2. analyse and evaluate communications and network infrastructures for enterprises;
3. use latest wired and wireless network technologies in building network infrastructures.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Networks and security

This unit present a coherent understanding of informational practices within organisations. It explores the structural and functional aspects that constitute organisational informatics and how these aspects combine to support diverse activities undertaken by organisations. The emphasis is to explore how information, and the ability to exploit it, contributes to corporate memory, enterprise knowledge and innovation in products, services and processes. Particular attention is given to diverse organisational setting to address private and public enterprises as well as third sector organisations.

On successful completion of this unit, students should be able to:

1. critically evaluate the concept of organisational informatics;
2. develop socio-technical approaches to organisational informatics practices;
3. analyse informational practices within organisations;
4. critique a range of theoretical and disciplinary influences on organisational informatics;
5. assess the extent to which technology can support informational practices.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • One 2-hour seminar
   • One 2-hour tutorial
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Archives and recordkeeping

Library and information science

This unit provides students with the skills and knowledge relating to the use of latest technologies for managing knowledge, electronic documents and records to meet the needs of individuals, work groups and organisations. The unit aims to build a general understanding of technologies for managing personal and organisational structured and unstructured information and knowledge and the methods of developing systems to handle it. Students study the business context, requirements analysis techniques and implementation issues for electronic document management, recordkeeping, content and other information and knowledge management systems.

On successful completion of this unit, students should be able to:

1. explain the value of implementing electronic information and knowledge management systems in various organisational contexts;
2. form and present professionally a credible opinion about emerging technological advancements and their relevance for information and knowledge management;
3. identify and select appropriate strategic options for designing and implementing an information and knowledge management system depending on the functional, non-functional and transitional user requirements;
4. conduct requirements identification, design and deployment of information and knowledge management systems for various users groups;
5. assess and synthesise diverse information about up-to-date information and knowledge management systems market and how to use implementation strategies to maximise their strengths and minimise their weaknesses.

Examination (2 hours): 40%; In-semester assessment: 60%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour tutorial
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • a minimum of 2-3 hours of personal study per one hour of contact time in order to satisfy the reading and assignment expectations.

See also Unit timetable information

Archives and recordkeeping

Library and information science

This unit provides students with a critical understanding of the impact of information technology (IT) within contemporary social relations. Using case studies drawn from different social spheres, the unit explores the ways in which the diffusion of IT has reshaped thinking and practice concerning social collaboration, the production of knowledge and community building. Particular attention is paid to the emerging field of community informatics, and the implications that this field holds for the work of information and knowledge management professionals.

On successful completion of this unit, students should be able to:

1. analyse the nature and operation of information communities within contemporary society;
2. evaluate community informatics as an emerging discipline and professional practice;
3. assess contemporary debates concerning the social impact of information technology use;
4. distinguish the collaborative behaviours and interdependencies which contribute to notions of community;
5. analyse and critique cases from the information industry.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%;

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour tutorial
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 2-3 hours of personal study per one hour of contact time in order to satisfy the reading and assignment expectations.

See also Unit timetable information

Archives and recordkeeping

Library and information science

This unit provides students with an understanding of the development and use of information systems that support managers, especially their decision-making tasks. Students will learn of the nature of management work and decision theory and how this affects the development of decision support systems. A number of commonly used decision support methods and techniques will be explored. Students will be introduced to personal decision support systems, group support systems, negotiation support systems, data warehousing, executive information systems and business intelligence.

At the completion of this unit, students will:

1. examine and describe the concepts, scope and application of IT for decision support;
2. explain the nature of managerial decision-making;
3. create IT-based decision support for managers;
4. evaluate major approaches of IT-based decision support;
5. select the appropriate decision support approach for a particular project;
6. perform system analysis for management support projects.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of tutorials
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit introduces students to the principles, techniques and applications of computer-based decision support models for business and industry. Topics include: decision trees; linear programming and optimisation; other mathematical programming methods; waiting lines and queues; time series analysis and forecasting; inventory modelling and discrete-event simulation. Models will be built and solved using spreadsheets or other computer applications as appropriate.

On completion of this unit, students should be able to:

1. explain a variety of techniques for modelling business decision problems;
2. choose the appropriate decision model for a particular problem;
3. set up simple models and solve with hand calculations;
4. set up mathematical models for solution in a spreadsheet or other application software;
5. validate models and conduct a sensitivity analysis;
6. analyse a real problem and report the results;
7. explain the difficulty of applying models to real situations - which often requires that approximations, simplifications and generalisations be made;
8. explain the approximate nature of some types of business modelling and why this usually means that a sensitivity analysis needs to be conducted.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours and 10 minutes): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Data science

The unit provides students with an overview of enterprise systems and is designed to describe the role of enterprise systems as part of the larger IT infrastructure within large scale organisations. A case study approach will be adopted which will focus on inherent issues surrounding management and deployment of enterprise systems, together with implementation issues influencing the impact of these systems on the organisation. SAP ECC6 will be the software of choice to introduce students to the complexity of enterprise resource planning systems through tutorial workshops.

On successful completion of this unit, students should be able to:

1. describe the role of enterprise systems in supporting the business strategy, business drivers and business requirements of various organisations;
2. identify the main suppliers, products and application domains of enterprise wide packages;
3. explain the scale and complexity of enterprise system packages with specific reference to enterprise resource planning systems in large scale organisations;
4. describe the integrative role of enterprise systems for information within the organisational context;
5. describe the role of enterprise systems as part of the larger IT infrastructure of large scale organisations;
6. identify the implementation variables, individual variables and contextual variables in enterprise system implementations and describe their role in achieving a successful implementation outcome;
7. use SAP ECC6 to demonstrate the complexity and integrative nature of an enterprise resource planning (ERP) system in a case organisation.

Examination (2 hours): 40%; In-semester assessment: 60%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour laboratory
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 2-3 hours of personal study per one hour of contact time in order to satisfy the reading and assignment expectations.

See also Unit timetable information

This unit develops understanding of information technology and information and knowledge management governance frameworks and strategy perspectives, with particular emphasis on the regulatory environment, legislative and organisational controls, audits, standards, professional certifications, and issues associated with measuring performance, demonstrating value and minimising risk. The unit builds on intellectual capital theory, augmented by insights from social capital and emotional capital. It draws on case studies to differentiate strategies focused primarily on people, business processes, and content, and considers the supporting technologies that can facilitate each approach.

On successful completion of this unit, students should be able to:

1. describe the characteristics and limitations of different IT and IKM governance frameworks and strategy perspectives, and how competing perspectives can be reconciled in practice;
2. evaluate the concepts underpinning the dominant intellectual capital perspective on IT and IKM strategy, the strengths and limitations of this approach, and how social capital and emotional capital insights can augment this view of strategy;
3. analyse the distinct features, the functional/disciplinary origins, and the key drivers of IT and IKM strategies focused primarily on (1) people, (2) business processes, and (3) content and technology, and the supporting technologies that can facilitate each approach;
4. analyse links between strategy, performance and measurement, and the issues associated with demonstrating the value and benefits of IT and IKM;
5. describe the nature of the IT and IKM regulatory environment and approaches to controlling risk;
6. evaluate the importance of marketing, leading and championing IT and IKM within the organisation, and of reflective practice.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour laboratory
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit provides a practical and theoretical understanding to what it means to be an information professional today. Students will encounter a range of issues relevant to professional practice in the workplace, including ethical and legal challenges caused by technology use. Through a fieldwork placement, students gain in-depth understanding of information agencies and the organisational environment in which they operate. Students will research established theories and concepts and critically evaluate their practical use (taking into account many international aspects) in organisations today, as well as reviewing and understanding the wider responsibilities that IT professionals are called upon to uphold in society. Topics addressed include - organisational and professional communication; teamwork; the nature of the information professions; the role of professional associations; problem solving and information use; cross-cultural awareness; personal and professional ethics and codes of practice. The unit addresses issues in information management and information systems currently identified by practitioners, managers, researchers, organisations, and academics as being of professional concern.

On successful completion of this unit, students should be able to:

1. compare and contrast IT professional roles, assessing the necessity and rationale for constant review and change;
2. identify and analyse the ethical dimensions associated with IT-related decisions, use and quality and their possible impacts on organisations and society;
3. reflect on and analyse the need for IT professional associations and the need for codes of ethics (including the ACS) in IT development and use;
4. research, select and apply strategies, protocols and innovative methods for effective and efficient communications across all stakeholders, evaluating their appropriateness for intercultural communications;
5. appraise and justify various teamwork skills for various situations, demonstrating the ability to apply them by working cooperatively and managing conflict within their team;
6. develop and apply appropriate information gathering, critical evaluation (information and its sources) and problem solving skills;
7. evaluate, assess and communicate both personal and team progress and learning, thus engaging in meaningful reflective practice.
8. apply theories and practice of selected specialisation to the workplace.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • One 1-hour lecture
   • One 2-hour tutorial
   • One 1-hour student meeting
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Archives and recordkeeping

Library and information science

This unit introduces students to the major categories of information resources in all media and how they are accessed through a variety of common user interfaces from anywhere in the world. The process of satisfying these needs through the reference interview and the application of skilled search strategies is explored. The ways that information resources are procured by libraries and e-repositories through purchase or licensing, and supplied to users on a cost-effective, efficient basis are examined. Access and authentication, intellectual property law and professional duty of care are described.

At the completion of this unit, students should be able to:

1. implement decisions about applying organisational policies for reference and collection services, justify the principles of collection management strategies, and evaluate them;
2. manage networked access for users in the case of electronic resources;
3. develop information literacy programs; and
4. select the best source of knowledge for a practical information need.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 1-hour seminar
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 9 hours independent study per week for completing tutorial and project work, private study and revision.

See also Unit timetable information

Library and information science

This unit develops understanding of the fundamental principles, concepts and standards that guide the development of information organisation and retrieval systems and web-based information architectures. It deals with standards governing description, distribution and access to information locally and globally cataloguing, indexing, thesaurus construction, classification and metadata for knowledge discovery. It examines the effects of economic, social and technological factors on the development of bibliographic networks and cataloguing operations. Practical sessions deal with the use of major bibliographic tools, schemes and systems for information organisation.

At the completion of this unit, students should be able to:

1. explain the key principles, concepts and standards that guide the development of information organisation and retrieval systems and web-based information architectures;
2. apply standard cataloging, classification, indexing, thesaurus construction, and knowledge discovery metadata schemes and tools;
3. explain the guiding principles behind bibliographic utilities/networks;
4. use bibliographic software; and
5. design systems for organising information and facilitating access to information resources in physical collections or digital/web-based repositories.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour laboratory
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Library and information science

This unit relates to managing the creation, storage, recall and dissemination of records. Recordkeeping is concerned with the management of information as evidence for accountability, transparency, memory and identity purposes. In order to achieve recordkeeping objectives it is essential to take individual, social (including organisational) and technological perspectives into account. Recordkeeping informatics is a continuum based approach to managing authoritative information in today's shifting, complex and technologically challenging environment.

At the completion of this unit, students should be able to:

1. Analyse the information culture of a workplace;
2. Apply business process analysis to recordkeeping;
3. Evaluate the ethical dimensions of recordkeeping frameworks, systems, policies and processes;
4. Design systems appropriate for the current recordkeeping requirements for specific organisaitons and communities.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One-2 hour tutorial
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing tutorial and project work, private study and revision.

See also Unit timetable information

Archives and recordkeeping

This unit enables students to read widely in a relevant topic within the fields of information technology, information systems or information management, under supervision. It may cover an area not offered in any other fifth-year level unit, or involve building greater in-depth knowledge in an area with which they already have some familiarity. Details for the reading unit will be defined and approved individually for each student and will include objectives, assessment details, due dates and an initial reading list. Assessment comprises a research paper or review (6000-10,000 words), project report, or equivalent. Enrolment into Reading Units and allocation of a supervising academic will be approved by the Associate Dean (Education).

At the completion of this unit, students will be able to:

1. analyse, synthesise and construct arguments from a range of published sources;
2. critique and evaluate others ideas, opinions and arguments;
3. explain ideas for scrutiny to a supervisor;
4. demonstrate self-reliance and time management skills in order to gain greater independence as a learner;
5. demonstrate the communication skills necessary to work effectively in a close, cooperative relationship with a supervisor.

Research assignment: 100%

Minimum total expected workload equals 12 hours per week. Students meet weekly with their supervisors for approximately 30 minutes to set goals and report on achievements and difficulties.

See also Unit timetable information

This unit enables students to pursue a particular topic of research in the fields of information technology, information systems or information management. The research is done under supervision, and provides a chance for a student to pursue a topic of interest that has not been covered in other coursework units, or to build more in-depth knowledge in an area with which they already have some familiarity but desire more knowledge and expertise. Students enrolling in this unit should have the approval of the Head of School or their nominee. Assessment comprises a research paper, project report, or equivalent.

At the completion of this unit, students will be able to:

1. analyse, synthesise and construct arguments from a range of published sources;
2. critique and evaluate others' ideas, opinions and arguments;
3. explain ideas for scrutiny to a supervisor;
4. demonstrate self-reliance and time management skills in order to gain greater independence as a learner;
5. demonstrate the communication skills necessary to work effectively in a close, cooperative relationship with a supervisor;
6. assess the nature and demands of independent research.

Research paper, review, project report or equivalent: 100%

Minimum total expected workload equals 12 hours per week. Students are expected to hold regular meetings with supervisor(s) over the course of the semester.

See also Unit timetable information

This industry experience studio project capstone unit gives students the opportunity to work in teams to research contemporary approaches to developing a defined project, develop new skills and apply the knowledge and skills they have already gained in a practical setting.

Teams will research and create a meaningful and beneficial problem space or design question and then carry out research or design in a systematic manner to develop and deliver a solution to industry standards, for use by organisations and/or community groups. Teams will be self managed and may be a mix of students drawn from all Masters courses in the faculty, depending on the specialist field.

Throughout this process students will need to communicate findings, knowledge and ideas effectively and professionally to a range of stakeholders, with a range of IT knowledge, in relevant and innovative ways. The stakeholders will include academics, peers, project-based stakeholders and senior industry experts. The students will attend unit seminars, carry out research individually and contribute in a professional, committed and collegial manner to the work of their team and studio peers.

At the completion of this unit, students should be able to:

1. critically analyse complex information relevant to an advanced specialist domain and identify information requirements interpreting how they may be of benefit to an organisation or a community;
2. analyse how specialist domain projects are developed and evaluate the underlying principles and reasons underpinning each aspect of the development process, proposing the need for and then using, a context driven methodological approach to deliver;
3. differentiate and synthesise the interrelated roles and responsibilities of all stakeholders of a project and assess and analyse why these roles are important for a successful project;
4. apply, in an industry standard setting, new concepts as well as aspects of theoretical approaches already learned, selecting the most appropriate fit for a specific situation and the rationale for that selection applying investigative research;
5. demonstrate discernment and judgment in effective two-way communication to all stakeholders/audiences, both specialist and generalist, by using innovative, relevant and meaningful mechanisms to disseminate knowledge and ideas;
6. contrast and apply the most suitable professional practice skills on issues relevant to the chosen area of practice and operate effectively as a member of that practice team;
7. evaluate, assess and communicate both personal and team progress and learning, thus engaging in meaningful reflective practice of one's self and the outcomes and process of the projects.

In-semester assessment: 100%

Minimum total expected workload equals 24 hours per week comprising:

1. Contact hours for on-campus students:
   • Two 1-hour seminar
   • Two 2-hour studio laboratories
   • Two 1-hour meeting times
2. Additional requirements (all students):
   • a minimum of 16 hours independent study per week for completing project work individually and with team members, client meetings and review work.

See also Unit timetable information

This unit provides a practical and theoretical understanding to what it means to be an IT professional today. Students will encounter a range of issues relevant to professional practice in the workplace, including ethical and legal challenges caused by technology use. Students will research established theories and concepts and critically evaluate their practical use (taking into account many international aspects) in organisations today, as well as reviewing and understanding the wider responsibilities that IT professionals are called upon to uphold in society. Topics addressed include - organisational and professional communication; teamwork; the nature of the IT professions; the role of professional associations; problem solving and information use; cross-cultural awareness; personal and professional ethics and codes of practice.

It is highly recommended that students enrol in FIT5122 in conjunction with FIT5120 where possible. Students therefore should take FIT5120 in the last semester of their course.

On successful completion of this unit, students should be able to:

1. compare and contrast IT professional roles, assessing the necessity and rationale for constant review and change;
2. identify and analyse the ethical dimensions associated with IT-related decisions, use and quality and their possible impacts on organisations and society;
3. reflect on and analyse the need for IT professional associations and the need for codes of ethics (including the ACS) in IT development and use;
4. research, select and apply strategies, protocols and innovative methods for effective and efficient communications across all stakeholders, evaluating their appropriateness for intercultural communications;
5. appraise and justify various teamwork skills for various situations, demonstrating the ability to apply them by working cooperatively and managing conflict within their team;
6. develop and apply appropriate information gathering, critical evaluation (information and its sources) and problem solving skills;
7. evaluate, assess and communicate both personal and team progress and learning, thus engaging in meaningful reflective practice.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 3 hours and 10 minutes.

Examination (3 hours): 25%, In-semester assessment: 75%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • One 1-hour lecture
   • One 3-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit aims to provide students with an advanced knowledge of IT security. Topics include design and implementation of advanced cryptosystems for high-performance applications such as low power mobile devices, cryptographic protocols for secure online computation applications such as e-voting. We will cover advanced hacking techniques, complete computer system penetration testing and defences. Further topics include advanced wireless network security, enterprise security architectures, malicious code detection and prevention systems, defence systems in depth, advanced software security, virtual system and cloud computing security, and emerging technologies such as quantum computing and cryptography. Students will do practical exercises and tasks throughout the unit.

On successful completion of this unit, students should be able to:

1. explain the operation of several advanced cryptosystems and protocols and their underlying assumptions and applications;
2. apply a range of hacking and penetration testing techniques;
3. describe advanced security design issues in the context of software and network settings;
4. explain the potential security implications and limitations of emerging technologies.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%, In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Networks and security

The aim of this unit is to prepare Masters students in the Faculty of Information Technology to conduct research across the range of IT disciplines, including computer science, software engineering, information systems and information management.

It introduces students to major research philosophies and paradigms, the principles of research design, research ethics, research methods and techniques of data collection and analysis appropriate to IT research and their disciplines, and IT research in research and industry settings.

Skills developed and knowledge acquired from this unit will prepare students to conduct and communicate their own research, as well as to be knowledgeable and critical interpreters of others' research.

At the completion of this unit, students should be able to:

1. identify and explain major research philosophies and paradigms;
2. design rigorous and ethical Masters level research projects and develop project proposals;
3. evaluate and select research methods and techniques of data collection and analysis appropriate to particular research designs, projects and disciplines;
4. conduct ethical research;
5. communicate research findings in written and oral form in research and industry settings;
6. critically review research literature, research design and reported findings;
7. apply research skills to operate effectively as a member of a research project team.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students: Two 2-hour workshops

2. Additional requirements (all students): A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit is a research unit common to FIT Masters degrees. Due to the nature of IT, a wide range of Masters project types can be offered to students. Some project components are of a practical nature and may involve software development and/or experimentation, while other components are of a more theoretical nature.

On completion of the Masters thesis, students will be able to:

1. design a rigorous Masters level research project and develop project proposal;
2. critically review research literature, research design and reported findings;
3. evaluate and select research methods and techniques of data collection and analysis appropriate to particular research designs, projects and disciplines;
4. conduct ethical research;
5. communicate research findings in written and oral form in research and industry settings.

This unit forms part of the sequence of units comprising the Masters Thesis in the Faculty of Information Technology.

The exit point is FIT5128 (18cpts). At the completion of the requirements for the thesis the following components of assessment will be completed:

Research Proposal: 5%; Literature Review: 10%; Interim Presentation: hurdle; Final Presentation: 5%;Thesis (normally 15,000 - 25,000 words): 80%

Minimum total expected workload equals 12 hours per week. Students will be expected to hold regular meetings with supervisor(s) over the course of the semester.

See also Unit timetable information

This unit is a research unit common to FIT Masters degrees. Due to the nature of IT, a wide range of Masters project types can be offered to students. Some project components are of a practical nature and may involve software development and/or experimentation, while other components are of a more theoretical nature.

On completion of the Masters thesis, students will be able to:

1. design a rigorous Masters level research project and develop project proposal;
2. critically review research literature, research design and reported findings;
3. evaluate and select research methods and techniques of data collection and analysis appropriate to particular research designs, projects and disciplines;
4. conduct ethical research;
5. communicate research findings in written and oral form in research and industry settings.

This unit forms part of the sequence of units comprising the Masters Thesis in the Faculty of Information Technology.

The exit point is FIT5128 (18cpts). At the completion of the requirements for the thesis the following components of assessment will be completed:

Research Proposal: 5%; Literature Review: 10%; Interim Presentation: hurdle; Final Presentation: 5%;Thesis (normally 15,000 - 25,000 words): 80%

Minimum total expected workload equals 12 hours per week. Students will be expected to hold regular meetings with supervisor(s) over the course of the semester.

See also Unit timetable information

This unit is a research unit common to FIT Masters degrees. Due to the nature of IT, a wide range of Masters project types can be offered to students. Some project components are of a practical nature and may involve software development and/or experimentation, while other components are of a more theoretical nature.

On completion of this unit, students will be able to:

1. design a rigorous Masters level research project and develop project proposal;
2. critically review research literature, research design and reported findings;
3. evaluate and select research methods and techniques of data collection and analysis appropriate to particular research designs, projects and disciplines;
4. conduct ethical research;
5. communicate research findings in written and oral form in research and industry settings.

This unit forms part of the sequence of units comprising the Masters Thesis in the Faculty of Information Technology.

The exit point is FIT5128 (18cpts). At the completion of the requirements for the thesis the following components of assessment will be completed:

Research Proposal: 5%; Literature Review: 10%; Interim Presentation: hurdle; Final Presentation: 5%;Thesis (normally 15,000 - 25,000 words): 80%

Minimum total expected workload equals 12 hours per week. Students will be expected to hold regular meetings with supervisor(s) over the course of the semester.

See also Unit timetable information

Enterprise networks are highly complex infrastructures that demand correct management practices in planning, operations and security. Significant challenges arise from the scale of operations required as well as the increasingly common incidents of intrusion, sabotage, espionage or data theft, and vandalism. The unit will provide students with practical foundations in planning secure networks, policy-based operations and the implementation of security. Students will also be introduced to best practices in dealing with security breaches. Practical skills will be acquired through lab activities and case studies (projects).

At the completion of this unit, students should be able to:

1. explain critical factors of enterprise security planning, operations and management;
2. perform risk analysis and assessment;
3. provide practical security policies, strategies and implementation plan for enterprise systems.

Examination (2 hours) 30%; In-semester assessment: 70%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory/tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Networks and security

Covers the core skills for enterprise architects, addressing the structuring and delivery of IT services in organisations. Addresses topics including SaaS, Cloud computing, enterprise 2.0 and other collaborative technologies, services science management and engineering and services strategy.

On the completion of this unit, students should be able to:

1. describe the purpose of enterprise architectures and the underlying principles of their design;
2. explain individual IT systems and services as interrelated components of an enterprise-wide platform;
3. implement knowledge of industry-standard enterprise architecture models, approaches, frameworks and standards;
4. describe into the need for sound data, information and technology governance strategies;
5. implement substantively to decisions regarding the design of an enterprise architecture for an organisation;
6. explain the alignment of an organisation's IT strategy, platforms and systems with the overall organisational strategy and management functions.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%, In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour tutorial
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit provides an introduction to the discipline of software engineering at the postgraduate level. The emphasis is upon a broad coverage of various aspects of software engineering. We assume the students will at this stage have adequate programming skills and are able to put theories to practice. The notion of a software system as a model or approximation of a desired system is introduced, and used as a way of describing such things as the software life cycle and its various models, programming by contract, design and testing issues, maintenance, reuse, complexity, divide and conquer strategies, metrics and measurement, project management and software legacy.

On successful completion of this unit, students should be able to:

1. describe the breadth and nature of the software engineering process and distinguish various phases of the process;
2. create and develop the required artifacts during each phase of the software engineering process;
3. differentiate and evaluate the software engineering techniques used to produce the artifacts;
4. assess the issues in constructing large software systems from its components, and the nature and design of these components;
5. employ group working skills in solving software development problems;
6. analyse and evaluate IT-related scenarios with reference to the software engineering code of ethics and professional practice.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit examines advanced database technology. This unit particularly covers three main types of advanced database technologies, including (i) document store, (ii) wide column store, and (iii) graph database. These three systems represent the broad spectrum of NoSQL databases. The underlying theoretical foundations, such as database modelling, transactions, and graph query processing will also be explored.

On successful completion of this unit, students should be able to:

1. describe various types of non-relational database systems, including NoSQL;
2. design and model document-store and wide column-store databases;
3. compare and contrast between relational and non-relational database modelling;
4. explain the concepts of transactions in non-relational systems;
5. implement document-store and wide column-store systems;
6. construct applications using a graph database system;
7. demonstrate graph query processing.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour laboratory
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit covers the core software engineering disciplines concerned with the design and development of complex software-based systems using advanced software engineering methods and technologies. This involves specification of software systems using advanced design languages and formal logics, as well as verifying the correctness of such specifications using formal engineering analysis methods and various mechanical/automated tools. Topics include design/modeling languages, software architecture design patterns, complex system design methods, mathematical logic, formal specification languages, theorem proving, and model checking. It shows how to analyse model complex software systems, how to express properties that the system should adhere to and how to use mechanical/automated tools to verify such properties.

On successful completion of this unit students should be able to:

1. define requirements for complex interactive software systems;
2. use modern high-level languages and technologies to document the architecture of complex reactive software systems;
3. design new a high-level domain-specific language for a specific domain;
4. articulate the central technical challenges of distributed reactive software systems and corresponding solution design patterns;
5. develop suitable architectural-level solutions for complex interactive software systems;
6. articulate the role of formal logic and verification methods in the system development life cycle;
7. categorise major techniques and approaches to software verification: theorem proving, model checking and model-based testing;
8. develop software specifications and express desirable properties using a formal language/logic such as the Event-B notation and temporal logics.

Examination (2 hours): 50%, In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing tutorial and project work, private study and revision.

See also Unit timetable information

Modern computer systems contain parallelism in both hardware and software. This unit covers parallelism in both general purpose and application specific computer architectures and the programming paradigms that allow parallelism to be exploited in software. This unit examines both shared memory and message passing paradigms in both hardware and software; concurrency, multithreading and synchronicity; parallel, clustered and distributed supercomputing models and languages. Students will program in these paradigms. This unit draws on units in distributed databases and grid computing. It will also cover the technology and application of cloud computing with particular reference to programming frameworks (e.g. MapReduce, Hadoop etc).

On successful completion of this unit, students should be able to:

1. solve basic problems in distributed computing, especially in relation to synchronisation, distributed transactions, concurrency control, distributed consensus;
2. explain the differences between various distributed computing models and widely used distributed computing schemes;
3. describe a variety of parallel programming paradigms, synchronisation and parallelisation primitives, message passing, data parallel, tuple space;
4. identify computational tasks that benefit from parallelism;
5. design and implement a parallel-distributed software system.

Examination (2 hours): 60%, In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing tutorial and project work, private study and revision.

See also Unit timetable information

This unit focuses theoretical concepts, applications and research issues of mobile software. Students will learn techniques to design and develop mobile applications. A number of different toolkits/development environments will be discussed and used for the practical component of the unit. Interaction between mobile applications and other systems such as sensor networks or web systems will also be explored.

On successful completion of this unit, students should be able to:

1. describe the principles and theoretical concepts of mobile software systems;
2. explain different mobile systems toolkits and development environments;
3. utilise techniques for developing mobile applications;
4. develop mobile applications;
5. integrate mobile applications with other systems, such as sensor network systems or web systems.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing tutorial and project work, private study and revision.

See also Unit timetable information

Computers and information technology pervade all aspects of modern society and industry. This unit is designed to familiarise students with several key ways in which IT technologies are increasingly being used. Currently tools based on data analytics, modelling, optimisation and visualisation are growing in relevance and application. This unit consists of a number of seminars, the content of which will cover key applications models and domains of the above techniques. The assessment component of this course is coursework only and in a series of assignments students will be required to undertake analytical research on recent developments in key application areas. Furthermore they will have the opportunities to develop skills in data management, data analytics and visualisation using state of the art tools such as R and Tableau.

Upon successful completion of this unit, students should be able to:

1. review and critique a range of information technologies as they are applied in real scientific and commercial environments. These include modelling, optimisation, visualisation, data analytics and simulations of complex systems;
2. articulate and explain how the management of data and storage can be made conducive to later data exploration and analysis;
3. analyse data sets and visualise the results of these analyses;
4. present the results of statistical data analysis to convey concrete information to non-technical users;
5. use a range of data analytics, visualisation and simulation tools including R;
6. apply theoretical understanding of novel IT techniques to real world community, business and scientific problems.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour studio
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing tutorial and project work, private study and revision.

See also Unit timetable information

Advanced methods of discovering patterns in large-scale multi-dimensional databases are discussed. Solving classification, clustering, association rules analysis and regression problems on different kinds of data are covered. Data pre-processing methods for dealing with noisy and missing data in the context of Big Data are reviewed. Evaluation and analysis of data mining models are emphasised. Hands-on case studies in building data mining models are performed using popular modern software packages.

On successful completion of this unit, students should be able to:

1. explain the kinds of data from which knowledge can be mined, the way each data type can be presented to a data mining algorithm, the kinds of patterns that can be mined from each data type;
2. evaluate the quality of data mining models;
3. perform pre-processing of large-scale multi-dimensional data sets in preparation for data mining experiments;
4. perform data pre-processing for data with outliers, incomplete and noisy data;
5. compare the various learning algorithms and the ability to effectively apply suitable algorithms to mine frequent patterns and associations from data, to perform data classification, data clustering and regression analysis;
6. use modern data mining tools to solve non-trivial data mining problems;
7. research the current trends in data mining applications;
8. work in a team to extract knowledge from a common data set using various data mining methods and techniques.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

The aim of this unit is to prepare Master of Philosophy students in the Faculty of IT to conduct research across the range of IT disciplines, including computer science, software engineering, information systems and information management.

It also provides PhD students with a foundation for their studies in FIT6021 Advanced IT research methods if they have not taken an equivalent unit in their previous studies.

It introduces students to major research philosophies and paradigms, the principles of research design, research ethics, research methods and techniques of data collection and analysis appropriate to IT research and their disciplines, and IT research in research and industry settings.

Skills developed and knowledge acquired from this unit will prepare students to conduct and communicate their own research, as well as to be knowledgeable and critical interpreters of others' research.

At the completion of this unit, students should be able to:

1. identify and explain major research philosophies and paradigms;
2. design rigorous and ethical Masters level research projects and develop project proposals;
3. evaluate and select research methods and techniques of data collection and analysis appropriate to particular research designs, projects and disciplines;
4. conduct ethical research;
5. communicate research findings in written and oral form in research and industry settings;
6. critically review research literature, research design and reported findings;
7. apply research skills to operate effectively as a member of a research project team.

In-semester assessment: 100%

Students will develop a portfolio of work linked to the workshops. It might include: critical reviews of research literature, design and findings; research proposals' workshop presentations; mini-research projects, practical exercises and quizzes relating to research design, methods and techniques; reflective blogs relating to the relevance of the workshops to their research thesis or project.

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two 2-hour workshops
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit is an elective designed for PhD and Master of Philosophy students. It focuses on the development of strategies and skills to complement and support PhD and Masters research studies, and prepare students for a career in research. PhD students are expected to complete FIT5144 before their Mid-Candidature/Progress Review.

On successful completion of this unit, students should be able to:

1. develop and implement a publication strategy;
2. manage research data and IP;
3. develop and implement research funding strategies;
4. apply entrepreneurial and innovative approaches to commercialising research;
5. communicate and publish research findings in different forms to a range of different audiences in academic, industry and community forums;
6. plan and organise PhD and Masters research, using the milestones to ensure timely completion;
7. apply a range of generic and professional research skills to enhance future employability and plan a career in research.

In-semester assessment: 100%

Each workshop, boot camp or other activity will include an associated assessable task, which will comprise a portfolio of results.

Equivalent of 48 hours of face-to-face contact/class time plus 96 hours of individual study time.

See also Unit timetable information

This unit looks at processes, case studies and simple tools to understand the many facets of working with data, and the significant effort in Data Science over and above the core task of Data Analysis. Working with data as part of a business model and the lifecycle in an organisation is considered, as well as business processes and case studies. Data and its handling is also introduced: characteristic kinds of data and its collection, data storage and basic kinds of data preparation, data cleaning and data stream processing. Styles of data analysis and outcomes of successful data exploration and analysis are reviewed. Standards, tools and resources are also reviewed. Basic curation and management are reviewed: archival and architectural practice, policy, legal and ethical issues.

On successful completion of this unit a student should be able to:

1. analyse the role of data in organisations, including curation and management issues;
2. apply basic tools for performing exploratory data analysis and visualisation;
3. apply basic tools for managing and processing big data;
4. apply basic predictive modeling and data analysis methods;
5. determine data storage and processing requirements for a data science project;
6. identify data resources and standards.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

For Monash Online: In-semester assessment: 100%

On-campus: Examination (2 hours and 10 minutes): 50%; In-semester assessment: 50%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures
   • Two hours/week laboratories
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions

   Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.

3. Additional requirements (all students):
   • A minimum of 8 hours per week of personal study (22 hours per week for Monash online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

This unit provides students with an understanding of the tasks and the main issues associated with the management of data in modern organisations and communities for business and societal purposes. The unit will examine some of the key issues that affect the data management function, incorporating recordkeeping, information accessibility, knowledge management and the governance and accountability for the data repositories. This will be used as a basis for explaining the nature of specialist work in this field and associated professional roles and responsibilities. Topics cover digital repository infrastructures, digital continuity planning; data archiving; data migration; the development of systems to support data discovery and reuse; mediated access to digital information; negotiation of data rights (ownership, copyright, access, privacy etc); utilisation of cloud computing platforms, and the data curation continuum.

On completion of this unit, students should be able to:

1. devise and propose a data curation strategy;
2. evaluate and critique existing data architectures and processes;
3. analyse and compare different approaches to delivering data services;
4. describe and explain ethical, legal, social and organisational issues that impact the creation and use of digital repositories;
5. recognise and describe specialist professional roles and responsibilities associated with digital repositories.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

For Monash Online: In-semester assessment: 100%

On-campus: Examination (2 hours and 10 minutes): 40%; In-semester assessment: 60%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures
   • Two hours/week tutorials
2. Contact hours for online (Caulfield) students:
   • Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
3. Contact hours for Monash Online students:
   • Two hours/week online group sessions
   • Monash online students do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
4. Additional requirements (all students):
   • A minimum of 8 hours per week of personal study (22 hours per week for Monash Online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

Archives and recordkeeping

Data science

Library and information science

This unit introduces statistical and visualisation techniques for the exploratory analysis of data. It will cover the role of data visualisation in data science and its limitations. Visualisation of qualitative, quantitative, temporal and spatial data will be presented. What makes an effective data visualisation, interactive data visualisation, and creating data visualisations with R and other tools will also be presented.

On successful completion of this unit, students should be able to:

1. perform exploratory data analysis using a range of visualisation tools;
2. describe the role of data visualisation in data science and its limitations;
3. critically evaluate and interpret a data visualisation;
4. distinguish standard visualisations for qualitative, quantitative, temporal and spatial data;
5. choose an appropriate data visualisation;
6. implement static and interactive data visualisations using R and other tools.

In-semester assessment: 100%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • One hour per week lecture
   • Two hours per week laboratories
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions
   • Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
3. Additional requirements (all students):
   • A minimum of 9 hours per week of personal study (22 hours per week for Monash online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

Advanced data analytics

Data science

Data engineering is about developing the software (and hardware) infrastructure to support data science. This unit introduces software tools and techniques for data engineering, but not hardware. It will cover:

• introduction to big data processing, covering volume, variety, and velocity;
• large volume data processing using parallel technologies;
• variety data formats, including unstructured and semi-structured data, using NoSQL databases;
• velocity data processing, covering data streaming;

On successful completion of this unit, students should be able to:

1. identify and assess big data concepts and technologies;
2. write and interpret parallel database processing algorithms and methods;
3. use big data processing frameworks and technologies;
4. describe and compare NoSQL technologies;
5. use and evaluate streaming methods in big data processing;
6. use big data streaming technologies.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

For Monash Online: In-semester assessment: 100%

On-campus: Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures
   • Two hours/week laboratories
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions.
   • Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
3. Additional requirements (all students):
   • A minimum of 8 hours per week of personal study (22 hours per week for Monash Online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

Advanced data analytics

Data science

This unit aims to provide students with the necessary analytical and data modeling skills for the roles of a data scientist or business analyst. Students will be introduced to established and contemporary Machine Learning techniques for data analysis and presentation using widely available analysis software. They will look at a number of characteristic problems/data sets and analyse them with appropriate machine learning and statistical algorithms. Those algorithms include regression, classification, clustering and so on. The unit focuses on understanding the analytical problems, machine learning models, and the basic modeling theory. Students will need to interpret the results and the suitability of the algorithms

On successful completion of this unit, students should be able to:

1. analyse data sets with a range of statistical, graphical and machine-learning tools;
2. evaluate the limitations, appropriateness and benefits of data analytics methods for given tasks;
3. design solutions to real world problems with data analytics techniques;
4. assess the results of an analysis;
5. communicate the results of an analysis for both specific and broad audiences.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

For Monash Online: In-semester assessment: 100%

On-campus: Examination (2 hours and 10 minutes): 50%; In-semester assessment: 50%

Minimum total expected workload equals 144 hours per semester comprising:

Contact hours for on-campus students:

• Two hours/week lectures.
• Two hours/week tutorials.

Contact hours for Monash Online students:

• Two hours/week online group sessions.
• Online students generally do not attend the lecture, tutorial and laboratory sessions, however, should plan to spend equivalent time working through resources and participating in discussions.

Additional requirements:

• A minimum of 8 hours per week of personal study (22 hours per week for Monash online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

Advanced data analytics

Data science

This unit provides detailed understanding of user interaction design theories, principles and practices and usability for web based systems and small screen devices. The unit examines issues in interaction design and usability from various perspectives, in particular the user experience. The unit includes how to achieve more effective design during systems development, tools and techniques for understanding users better and the application of these to designing web and small screen device systems. It explores contemporary issues including the challenges faced by designers with emerging technologies.

At the completion of the unit, students should be able to:

1. use and explain HCI theories, principles and guidelines;
2. identify and analyse the elements, controls and constraints of effective user interfaces in different platforms;
3. design and justify a useful and usable interface by applying user-centred design principles;
4. critically evaluate and assess a user interface and provide recommendations.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour laboratory
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit provides students with an understanding of the development and use of IT tools and techniques for modelling and decision support in the field of finance. The unit is designed to give students a broad understanding of the financial subsystems confronting business enterprises. The main focus, besides the traditional modelling of finance decision making process using spreadsheet tools, will be IT tools and related techniques that can aid in the analysis and interpretation of real financial problems confronting an enterprise. This unit will look at business related financial issues in the context of specific case studies.

On the completion of this unit, students should be to:

1. explain the core foundations of finance, as appropriate to key financial analysis and decision making;
2. analyse the core technologies that support financial analysis and decision making;
3. implement quantitative techniques supporting financial analysis and decision making;
4. apply the technologies and techniques studied to solving financial issues;
5. analyse financial solution requirements and select appropriate technical and quantitative decision aids;
6. interpret outputs from quantitative and technology based finance tools to aid in decision making.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Business processes must be designed to ensure that they are effective and meet customer requirements. A well-designed process will improve efficiency and deliver greater productivity. This unit will introduce students to analytical tools that can be used to model, analyse, understand and design business processes. Students will also gain hands-on experience in using simulation software as a tool for analysing business processes.

On successful completion of this unit, students should be able to:

1. describe business processes, their structures and how they fit in to the overall organisation objectives;
2. use analytical tools for modelling, analysing, understanding and designing business processes;
3. use simulation software as a tool for analysing business processes;
4. report to and advise management on business process design and re-engineering issues.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours lectures
   • Two hours tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

The unit aims to provide the students with in depth knowledge of techniques required to deal with security problems in information systems. The main areas of study include symmetric and asymmetric encryption techniques, cryptographic hash functions with related topics of message authentication codes and digital signatures. Study of techniques and algorithms for providing mutual trust include key management and distribution and user authentication to establish trust in the identity of communicating partner are also included. It looks at various management issues, including use and abuse of encryption, distributed systems authentication and integrity management. A range of security applications are used as examples. Students will learn how to apply cryptographic techniques in practice.

At the completion of this unit, students should be able to:

1. critically assess threats, vulnerabilities and risks to an organisation's information assets, and propose control technologies and techniques which can be applied to reduce the security risk;
2. apply a variety of cryptographic algorithms to develop methods to disguise information to ensure its integrity, confidentiality and authenticity;
3. apply a variety of methods for key management and distribution and analyse the risks associated with the various approaches;
4. implement user authentication and access control mechanisms to create a security architecture to protect the assets of the information system;
5. implement cryptographic techniques to preserve the security of information and evaluate its effectiveness;
6. apply a variety of security control technologies to IT systems in an organisation.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing tutorial and project work, private study and revision.

See also Unit timetable information

This unit presents students with the theory and practice underlying computerised information retrieval. Topics covered include: history and context of information retrieval systems, retrieval models, Boolean, vector space and probabilistic, evaluation strategies, test collections, web search engines, indexing, content-based multimedia retrieval and relevance feedback.

At the completion of this unit, students should be able to:

1. analyse critically the context and application of information retrieval systems;
2. compare the different models of information retrieval and their comparative advantages and disadvantages;
3. apply objective and subjective evaluation strategies in information retrieval systems;
4. address the issues and challenges of managing very large collections of heterogeneous data for information retrieval;
5. research how web search engines and search algorithms are constructed, utilised and deployed;
6. do indexing for different media;
7. implement information retrieval systems for the retrieval of audio-visual information;
8. reflect on the theoretical and practical underpinnings of relevance feedback in information retrieval systems.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit focuses on the design and programming techniques essential for developing distributed software systems and applications - with Java as the teaching language. The unit presents concurrent programming primitives and concepts for distributed systems. The unit also focuses on application of concurrent techniques in distributed system designs. Programming and implementation issues and techniques of distributed applications are studied. Enabling techniques for building distributed systems are analysed and evaluated. Distributed Software Patterns are presented. The unit also includes case studies of distributed programming paradigms and their applications (e.g. JINI, JavaSpaces).

At the completion of this unit, students should be able to:

1. analyse critically and reflect on the concepts and characteristics of distributed and concurrent software;
2. identify and evaluate common distributed and concurrent software designs;
3. design distributed software applications using typical distributed software architectures;
4. write distributed and concurrent software programs.

Examination (2 hours plus 30 minutes reading and noting time): 50%, In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit covers the core software engineering disciplines concerned with managing and delivering quality software. Topics include processes, tools and techniques for system validation and verification, including major commercial tools used in industry. It shows how to detect, analyse and control defects in complex software systems. Inspection and testing methodologies, analysis of artefacts, robustness, quality assurance, and advanced software validation and verification methods are covered.

On successful completion of this unit, students should be able to:

1. explain the importance of quality assurance in software engineering;
2. articulate the role of validation and verification methods in the system development life cycle; key issues in software testing, testing levels and testing techniques;
3. categorise and apply selection and combination of techniques and test related measures;
4. measure, evaluate and analyse software under test using different quality and complexity metrics;
5. develop adequate test cases to help detect software system defects using industry-strength IDEs, unit testing frameworks such as JUnit, code coverage tools such as Cobertura, and other similar products;
6. implement continuous integration (CI) at unit, integration & system testing level using a CI server such as Jenkins to automatically run regression test suites on the system under test.

In-semester assessment: 50%; Examination (2 hours): 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing tutorial and project work, private study and revision.

See also Unit timetable information

This unit focuses on four of the important knowledge areas established from the Project Management Body of Knowledge (PMBOK): scope management, time management, cost management and quality management.

The unit demonstrates the technical aspects of the knowledge areas otherwise known as the triple constraints - and places the emphasis on the planning and execution of projects. The unit will demonstrate how the triangulation of these knowledge areas supports a successful project. The unit will conclude with a discussion on governance compliance and decision making techniques to provide traceable project transparency and accountability.

On successful completion of this unit, students should be able to:

1. critically evaluate the synchronicity between the main four knowledge areas as outlined in PMBOK - scope, time, budget and quality - in order to evaluate project performance;
2. critically analyse and transform complex project management problems by using a range of project management evaluation tools, financial techniques and modern software that are involved with the four main knowledge areas;
3. demonstrate expert judgment and adaptability when presented with specialised technical project management issues.

Examination (3 hours): 40%, In-semester assessment: 60%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Project management

This unit provides a high level coverage of mobile and distributed computing. It will focus on the underlying concepts and standards of mobile computing and current technologies for mobile and distributed systems. It will discuss cellular networks, wireless networks and their standards and technologies, context-aware computing, location-awareness, wireless sensor networks, internet mobility, web services and service-oriented technology, cloud computing and current research trends and case studies.

At the completion of this unit students will:

1. identify and describe different approaches and methods for building distributed and mobile computing systems;
2. evaluate several models and approaches and select suitable mobile computing solution to a particular case;
3. propose and develop a mobile or distributed system that is appropriate to a problem domain;
4. identify the current research directions in the field and their impacts.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit introduces main techniques widely used in intelligent software systems to students in the Master of Information Technology Systems course with the Network Computing major. Specifically, it focuses on the techniques in relation to network structures. Main topics covered include neural network models, supervised learning and classification, unsupervised learning and clustering, fuzzy logic, intelligent decision analysis, optimum network flow modelling, and recommender systems.

On completion of this unit, students will have a knowledge and understanding of:

1. Explain the principles and theoretical underpinning of intelligent systems
2. Develop intelligent models and conduct experiments for solving a specific problem
3. Describe and evaluate the advantages and limitations of intelligent models and techniques for solving a wide range of practical problems
4. Analyse and evaluate current research developments in intelligent systems

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit will review the basic concepts of networking technologies and analyse technological aspects of the wireless network. Main topics will include: antenna and propagation for wireless systems, fundamentals of physical layers used in wireless networks, wireless local area networks (WLAN/WiFi), WiMax systems, mobile network technologies (3G and LTE), mesh networks. Unit will also cover advanced topics in wireless networking.

At the completion of this unit students will be able to:

1. describe the basic characteristics of layered protocol networking model and wireless mobile systems;
2. describe wireless network architecture and signal characteristics of cellular communication systems;
3. analyse physical and media access control layers used in wireless technologies for signal encoding, spread spectrum and error control;
4. describe architectures of: WiFi, WiMax, and advanced mobile networking systems like LTE as described in relevant standards
5. analyse and interpret concepts behind mesh networks
6. analyse advance topics in wireless networking.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory/tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit introduces students to IT research. Specifically, it introduces major research methods that are used by IT researchers including experiments, surveys, case studies, and design science. It also addresses the collection and analysis of quantitative and qualitative data. Students will learn how to effectively communicate research. Skills developed and knowledge acquired from this unit will prepare students to conduct their own research, as well as to be knowledgeable consumers of others' research.

On completion of this unit, students will be able to understand:

1. Explain the major philosophies and principles of research
2. Apply the major research methods used in IT research
3. Select and justify an appropriate research methodology for a research project
4. Collect and analyse quantitative and qualitative research data
5. Communicate research findings, orally and in writing, to a variety of audiences review and critique IT research literature and research design
6. Plan, design and develop a research project

In-semester assessment (assignments and class tests): 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour studio/tutorial
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Module 1: In-depth coverage of the protocols used to operate the Internet and intranets, and a selection of major applications, including specific implementations of the protocols and systems. The topics include: Advanced Internet Addressing: IPv6, subnetting, supernetting. TCP Performance and Enhancements: Reno, New-Reno, Fast Retransmit and Recovery, etc. Unicast and multicast routing protocols: BGP4, OSPF, MOSPF, DVMRP, etc. Messaging systems: SMTP, MIME, POP3, IMAP, World Wide Web systems: client-server implementations, HTTP, Real Time Protocols: RTP, RTCP,RSVP. Security and Firewall. Quality of Service issues: DiffServ and IntServ. Network management and Remote File activities.

Module 2: This unit aims to provide students with fundamental knowledge of network and information security. Topics to be covered include network components and services, network computer systems and security policy, security at different system layers, basic cryptography and information security, information security and communications, intrusion detection system, malicious code and detection and prevention systems, authentication systems, and wireless security.

On successful completion of this unit, students should be able to:

1. interpret complex information contained in the networking protocol standards;
2. analyse and evaluate details of the network protocols related to the: data link network, transport and application layers;
3. evaluate parameters of the data transfer through the local area, backbone, metropolitan and wide area network;
4. analyse and evaluate multimedia networks and network management systems;
5. critically assess threats, vulnerabilities and risks to an organisations' networks and synthesise alternatives with estimates of their effectiveness;
6. conduct forensic analysis of the system when a security breach takes place.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

10 hrs lectures/wk, 10 hrs tutorials/wk for 5 weeks

See also Unit timetable information

This unit is composed of two modules. The first module provides students with an understanding of the design and development of systems that support the large enterprise in a web-based environment. Students will learn of the theoretical issues that need to be considered by the enterprise and how they can affect the development of the enterprise application. A number of techniques will be introduced as the technological means to build such an application with specific emphasis on the Java EE technology.

The second module of this unit provides students with the knowledge, understanding and skills required to develop an application system, which uses a web interface to a back-end database. The unit assumes a sound basic knowledge of programming and database concepts and skills as developed in the introductory units in these areas. The emphasis in the unit is on mastery of the key concepts and the basic knowledge and skills required to build this kind of application. The unit will provide students with an awareness of the wide range of technologies which are used to support this kind of application, but will examine only a limited number of these technologies to demonstrate the key concepts and their application.

This unit will take a strongly practical focus in examining the technology issues involved, and highlight the key issues which a developer needs to address in developing applications of the kind for real-world systems.

On successful completion of this unit, students should be able to:

1. analyse various web environments and their components, and assess issues pertaining to enterprise software architecture on the web;
2. analyse the principles for developing web applications of varying size and complexity, and apply advanced design principles;
3. interpret and test the key features of programming languages which are commonly used for developing enterprise level web applications;
4. describe various advanced Java technologies used to build web applications, and competently apply the advanced Java libraries to build a medium-size web application for the enterprise;
5. describe various advanced ASP.NET technologies used to build web applications, and apply the advanced C# libraries to build a medium-size website using the MVC design pattern;
6. analyse and critique the key technological issues confronting developers building web applications.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 3 hours and 10 minutes.

Examination (3 hours): 50%; In-semester assessment: 50%

10 hrs lectures/wk, 10 hrs laboratories/wk for 5 weeks

See also Unit timetable information

This unit together with FIT5057 provides a holistic approach to project management. The emphasis of this unit is on theoretical foundation of project management in global environment, and adequate level of understanding of skills necessary for people to be involved in and managing projects globally. The practical exercises and relevant case studies will familiarize students with as many of current issues/problems/solutions as possible, and thus increase their ability to recognize the potential pitfalls in managing projects globally and provide appropriate solutions for them.

On successful completion of this unit, students should be able to:

1. analyse and evaluate theories and concepts of program and portfolio project management in a global context;
2. assess and synthesise diverse information regarding the ways of achieving maturity in global project management;
3. evaluate innovative ideas and strategies for managing global projects;
4. demonstrate and modify relevant software methodologies in creating and managing project databases;
5. develop professional/personal skills - team work; leadership; ethical behaviour; analytical skills, including lateral problem solving and critical thinking.

Examination (2 hours): 40%; In-semester assessment: 60%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour tutorial
2. Study schedule for off-campus students: Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.

3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing tutorial and project work, private study and revision.

See also Unit timetable information

Project management

This unit is intended to provide students with a framework for understanding business intelligence systems as well as the provision of high quality, integrated data for decision support through data warehousing. The unit has a particular focus on the evolutionary process of developing data warehousing using relational database management systems, and multi-dimensional modelling for structuring business intelligence data. The unit also presents students with coverage of several important aspects of data warehousing, including architecture, design, implementation, and optimisation. The unit will present this material using relevant research, case studies and practical exercises. Students will develop data warehouse modelling and OLAP using relational database management systems.

On successful completion of this unit, students should be able to:

1. describe the scope and application of data warehousing
2. design data warehousing systems
3. design multidimensional data models using star schemas
4. implement data warehousing in relational databases
5. use OLAP in SQL
6. explain the need for data warehousing architecture
7. explain query optimisation and its impact on multi-dimensional design

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour laboratory
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit introduces tools and techniques for data wrangling. It will cover the problems that prevent raw data from being effectively used in analysis and the data cleansing and pre-processing tasks that prepare it for analytics. These include, for example, the handling of bad and missing data, data integration and initial feature selection. It will also introduce text mining and web analytics. Python and the Pandas environment will be used for implementation.

At the completion of this unit, students should be able to:

1. parse data in the required format;
2. assess the quality of data for problem identification;
3. resolve data quality issues ready for the data analysis process;
4. integrate data sources for data enrichment;
5. document the wrangling process for professional reporting;
6. write program scripts for data wrangling processes.

In-semester assessment: 100%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures
   • Two hours/week tutorials
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions
   • Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
3. Additional requirements (all students):
   • A minimum of 8 hours per week of personal study (22 hours per week for Monash Online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

This unit explores the statistical modelling foundations that underlie the analytic aspects of Data Science. Motivated by case studies and working through examples, this unit covers the mathematical and statistical basis with an emphasis on using the techniques in practice. It introduces data collection, sampling and quality. It considers analytic tasks such as statistical hypothesis testing and exploratory versus confirmatory analysis. It presents basic probability distributions, random number generation and simulation as well as estimation methods and effects such as maximum likelihood estimators, Monte Carlo estimators, Bayes theorem, bias versus variance and cross validation. Basic information theory and dependence models such as regression and log-linear models are also presented, as well as the role of general modelling such as inference and decision making, and predictive models.

At the completion of this unit, students should be able to:

1. perform exploratory data analysis with descriptive statistics on given datasets;
2. construct models for inferential statistical analysis;
3. produce models for predictive statistical analysis;
4. perform fundamental random sampling, simulation and hypothesis testing for required scenarios;
5. implement a model for data analysis through programming and scripting;
6. interpret results for a variety of models.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Monash Online: In-semester assessment: 100%

On-campus: Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures
   • Two hours/week laboratories
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions.
   • Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
3. Additional requirements (all students):
   • A minimum of 8 hours per week of personal study (22 hours per week for Monash online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

This unit introduces machine learning and the major kinds of statistical learning models and algorithms used in data analysis. Learning and the different kinds of learning will be covered and their usage will be discussed. The unit presents foundational concepts in machine learning and statistical learning theory, e.g. bias-variance, model selection, and how model complexity interplays with model's performance on unobserved data. A series of different models and algorithms will be presented and interpreted based on the foundational concepts: linear models for regression and classification (e.g. linear basis function models, logistic regression, Bayesian classifiers, generalised linear models), discriminative and generative models, k-means and latent variable models (e.g. Gaussian mixture model), expectation-maximisation, neural networks and deep learning, and principles in scaling typical supervised and unsupervised learning algorithms to big data using distributed computing.

On successful completion of this unit, students should be able to:

1. describe what statistical machine learning and its theoretical concepts are;
2. assess a typical machine learning model and algorithm;
3. develop, and apply major models and algorithms for statistical learning;
4. scale typical statistical learning algorithms to learn from big data.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

On-campus: Examination (2 hours) 50%; In-semester assessment 50%

Monash Online: In-semester assessment: 100%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures
   • Two hours/week laboratories
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions
   • Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
3. Additional requirements (all students):
   • A minimum of 8 hours per week of personal study (22 hours per week for Monash Online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

Advanced data analytics

This unit focuses on big data processing, including latest big data technologies (Spark), and NoSQL database (MongoDB). The data processing covers data frames, and various advanced data analytics for big data. Programming exercises and assignments use Spark, MongoDB, Data Frames, and ML Lib.

Upon successful completion of this unit students should be able to:

1. identify and explain big data technologies;
2. apply parallel processing using Spark and Data Frames;
3. use and evaluate NoSQL databases;
4. apply common data analytics and machine learning algorithms in a big data environment;
5. evaluate the suitability of different processing techniques for big data processing.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

On-campus:

Examination (2 hours): 60%; In-semester assessment: 40%

Monash Online:

In-semester assessment: 100%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures
   • Two hours/week laboratories
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions.

   Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.

3. Additional requirements (all students):
   • A minimum of 8 hours per week of personal study (22 hours per week for Monash Online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

Data science

In the digital world, how we communicate, conduct business and socialize is revolutionising our way of life. The explosion of data and discovery are transforming the way we live and work, altering relationships between government and citizens, businesses and consumers, the researchers and the researched, the public and private sectors, the individual and society. This unit explores how big data analytics can potentially help grow the economy, improve health and education, support national security, protect the environment, enable more energy efficiency, drive innovation and progress, and support more resilient, sustainable communities and cultures. It also addresses the risks associated with the application of big data analytics in government and big business to support greater surveillance of citizen by state and consumers by business, disempower individuals and vulnerable communities, support discrimination, threaten social inclusion, social justice, human and civil rights, self-determination and privacy, and widen the divide between the data haves and have-nots.

The unit will cover: introduction to social, cultural and heritage informatics; building digital media/data ecosystems and using data technologies to achieve the benefits and mitigate the risks of big data; developing socio-legal and policy frameworks to ensure transparency, good governance, accountability and ethical practice; big data rights regimes - rights in data, rights to self determination, privacy rights, access rights, discovery rights, IP and copyright; use of big data to support resilient, sustainable communities and cultures.

At the completion of this unit, students should be able to:

1. explain social, cultural and heritage informatics;
2. describe and analyse digital media/data ecosystems;
3. analyse issues relating to the benefits and risks of big data in society;
4. investigate how rights in data, rights to self determination, privacy rights, access rights, discovery rights, IP and copyright apply in different contexts/scenarios;
5. develop recommendations for socio-legal and policy frameworks and strategies for transparency, good governance, accountability and ethical practice in data management and use, including data rights management;
6. analyse needs and issues relating to the use big data to support resilient, sustainable communities and cultures.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours lectures
   • Two hours laboratories
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
3. Additional requirements (all students):
   • A minimum of 8 hours of personal study per week for completing lab/tutorial activities, assignments, private study and revision.

See also Unit timetable information

Archives and recordkeeping

Data science

Library and information science

Maintaining continuity in a digital data driven world is emerging as a key challenge for organisations, communities, governments and societies. Digital continuity is defined as the ability to use digital information in the way that is needed for as long as it is needed. It encompasses understanding the frameworks, principles, processes and technologies underpinning intergenerational system conceptualisation, design, development and implementation.

This unit will build on the introduction to digital/data curation provided in FIT5146. It will examine the laws, frameworks and policies for managing and preserving digital media and data as evidence and cultural heritage; access and appraisal strategies, policies and tools, metadata regimes for digital media and data archives; digital repository platforms, technologies, systems and tools; management of archival databases, datasets and digital media collections; and development and deployment of digital media and data archiving tools and services for users. Exemplar digital media and/data archiving initiatives and projects in the community and cultural heritage sectors will also be explored.

At the completion of this unit, students should be able to:

1. explain the role that records and archives play in organisations and society;
2. evaluate and apply archival frameworks, policies and best practice for the preservation of digital resources as evidence, memory and cultural heritage;
3. specify functional requirements for and evaluate digital repository platforms, technologies, systems and tools;
4. identify and evaluate digital archiving tools and services for users;
5. evaluate digital archiving initiatives/projects in the community and cultural heritage sectors.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours lectures,
   • Two hours tutorials
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
3. Additional requirements (all students):
   • A minimum of 8 hours of personal study per week for completing lab/tutorial activities, assignments, private study and revision.

See also Unit timetable information

Archives and recordkeeping

Data science

This unit is a research unit for students in the Graduate Certificate in Information Technology Research. Due to the nature of IT, a wide range of project types can be offered to students. Some project components are of a practical nature and may involve software development and/or experimentation, while other components are of a more theoretical nature.

On completion of this unit, students will be able to:

1. design a rigorous Masters level research project and develop project proposal;
2. critically review research literature, research design and reported findings;
3. evaluate and select research methods and techniques of data collection and analysis appropriate to particular research designs, projects and disciplines;
4. conduct ethical research;
5. communicate research findings in written and oral form in research and industry settings.

At the completion of the requirements for the thesis the following components of assessment will be completed:

Research Proposal: 5%; Literature Review: 10%; Interim Presentation: hurdle; Final Presentation: 5%; Thesis (normally 15,000 - 25,000 words): 80%

Minimum total expected workload equals 36 hours per week. Students will be expected to hold regular meetings with their supervisor(s) over the course of the semester.

See also Unit timetable information

This unit introduces students to problem solving concepts and techniques fundamental to the science of programming. It covers data types; data structures; algorithms; algorithmic complexity; and recursion. Detailed topics include analysis of best and worst-case time complexity; data structures such as lists, stacks, queues, binary search trees, graphs and heaps; hashing; sorting algorithms; searching algorithms; and graph algorithms. Students will implement these algorithms and data structures in the Python programming language.

At the completion of this unit, students should be able to:

1. design and implement simple algorithms in Python;
2. implement basic data types such as stacks, queues, lists, trees, priority queues, heaps and hash tables;
3. compare and evaluate different algorithms and implementations of basic data types;
4. calculate best case and worst case big-O algorithm complexity.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hour lectures
   • One hour tutorial
   • Two hour laboratory
2. Additional requirements (all students):
   • A minimum of 7 hours of personal study per week in order to satisfy the reading, lab and assignment expectations.

See also Unit timetable information

Semi-structured data is one of the fastest growing kinds of data in both the public and private sector, for instance in health. Email collections with sender-recipient graphs, metadata and text content is one example. This unit will explore basic forms of semi-structured data: text, time-sequence data, graphs and multiple relations in a database. Basic machine learning algorithms for these kinds of data will be analysed and applied. Some characteristic industry problems for the application of semi-structured data will also be investigated such as cohort analysis and market-basket analysis.

At the completion of this unit, students should be able to:

1. appraise what kinds of semi-structured data exist and the problems they present for analysis;
2. analyse different kinds of algorithms for different kinds of semi-structured data;
3. develop and modify some standard algorithms for semi-structured data;
4. examine some characteristic industry problems involving semi-structured data, and analyse the suitability of different algorithms.

Examination (2 hours, plus 30 minutes reading and noting time): 50%; in-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

• Two hours/week lectures
• Two hours/week laboratories

A minimum of 8 hours per week of personal study (22 hours per week for Monash Online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

This unit gives students the opportunity to work in teams in order to acquire hands on experience in advanced data analytics, develop new skills, and apply the knowledge and skills they have already gained in a practical setting.

Teams will be given real or simulated data sets pertaining to real-world problems, and will apply advanced data analytics techniques in order to develop models over the data and to derive from these meaningful insights. Teams will be self-managed and will perform work by use of standard collaboration tools.

Throughout this process students will need to communicate findings, knowledge and ideas effectively and professionally to a range of stakeholders. The stakeholders will include academics, peers, project-based stakeholders and industry experts. The students will use these communicated findings in order to direct and further their research throughout the process, as well as to divide work in ways that will allow each student to carry out research individually.

Students will be ranked both on the performance of their teams (the quality of the insights and the models, and the ability to visualise and communicate findings to stakeholders) and on their individual performance (professionalism, commitment and collegiality of joint work, quality of research undertaken).

Upon successful completion of this unit students should be able to:

1. critically analyse a business problem and translate it into a data science problem via interrogation of business stakeholders, with the purpose of ascertaining the underlying business realities and validity of the translation;
2. determine, in conjunction with business stakeholders, agreed methods of evaluation of solutions to-be-derived for the business problem, and critically assess them for their quality, practicality and difficulty of implementation;
3. critically evaluate available data for its sufficiency for the investigation of a given data science problem, and supplement it with external data where appropriate;
4. apply, in an industry standard setting, studied skills of data wrangling, data integration, imputation, model building, validation and optimisation, selecting the most appropriate tool for every situation, in order to derive a satisfactory solution to the business problem;
5. demonstrate discernment and judgement in effective two-way communication to all stakeholders/audiences, including for communicating the final problem solution, recommendations for its implementation, its projected impact on the business, and any insights derived as part of the project;
6. operate effectively as a member of a data analytics team, such as by effective intra-team communication, task assignment, progress communication and overall goal alignment.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

• One weekly 1-hour meeting with academic and/or industry project stakeholders.
• One 3-hour workshop/meeting every week, including 3 meetings with relevant stakeholders for communication of (interim) findings and review.
• a minimum of 8 hours independent research per week, for completion of case study analysis work individually and together with other team members.

See also Unit timetable information

Data science

Data analytics

Blockchain is regarded as the next revolution of Internet. Applications are not just limited to cryptocurrencies such as Bitcoin, but also extended to different interdisciplinary sectors. This unit is for students to develop basic knowledge of blockchain technology and how they can be used in real-world scenarios such as payment systems or supply-chain management. Learning activities will focus on understanding different blockchain systems, a broad landscape of supervised and unsupervised learning methods with a focus on the state-of-the-art knowledge for blockchain technologies including consensus, privacy-preserving protocols and smart contract which are rapidly used in different industries.

Upon successful completion of this unit students should be able to:

1. Evaluate the basic structure of a blockchain system, what is involved in designing such systems and strategy to maintain them.
2. Assess what consensus protocol is, what makes consensus work, and the limitation of each consensus protocol.
3. Investigate methods to preserve privacy for user and data in a blockchain system.
4. Demonstrate how blockchain systems can be applied into different disciplines such as healthcare, supply-chain.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

• Two hours/week lectures
• Two hours/week laboratories

A minimum of 8 hours per week of personal study for completing lab/tutorial activities, assignments, private study and revision

See also Unit timetable information

The aim of the unit is to prepare PhD candidates from the Faculty of IT to conduct research across the range of the disciplines that cover Information and Communication Technology (ICT) research, including computer science, software engineering, at the technical end, and organisational and social informatics, which address societal needs in ICT. This unit is compulsory for all students enrolled in the FIT PhD program.

The unit comprises five workshops, which address the broad philosophical, methodological and ethical underpinnings of conducting research in ICT, as well as classical and modern approaches to designing data collection and analysis for rigorous and sophisticated ICT research studies. Students have the option to choose from a list of available workshops.

Upon successful completion of this unit, students should be able to:

1. design rigorous and ethical research studies;
2. conduct high quality independent ICT research;
3. assess research design across a range of research strategies and paradigms;
4. consider and evaluate appropriate data collection instruments, and sampling strategies to fit the research purpose;
5. understand the key principles of ethical and professional research conduct;
6. understand the key principles of research presentation.

In semester assessment: 100%

Each workshop will include an associated assessable task, which will comprise a portfolio of results to contribute 20% to the final assessment. These will comprise written and oral presentations to be performed individually and/or in groups. To pass this unit, students must achieve at least a total mark of 70% from five workshops, and must achieve at least 50% in each workshop.

Each workshop has seven hours of face-to-face contact plus 24 hours of individual study time per semester.

See also Unit timetable information

The unit provides a basic introduction to fundamental information systems concepts including basic business concepts, information technology strategy and governance, sourcing, the different kinds of IT systems at both enterprise and desktop scales, introduction to architectures and professional practice and introductory project management.

On successful completion of this unit, students should be able to:

1. discuss key considerations of strategic business contexts relevant to managing IT resources in an organisation;
2. evaluate common business processes and the role IT can play in managing these processes;
3. apply a generic model of the systems development lifecycle to plan and manage deliverables and milestones during information systems design and development;
4. discuss contract development and select an appropriate sourcing strategy for provisioning information systems;
5. analyse factors relevant to managing small to medium-sized projects for in-house or contract software development, software outsourcing, package acquisition and implementation;
6. identify the requirements for ongoing management of IT infrastructure in an organisation;
7. discuss key considerations in strategically planning for technological innovation to meet the short and long-term business objectives of an organisation;
8. discuss ethical and professional issues relevant to members of the IT profession;
9. discuss ethical issues related to the management and use of IT in organisations.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour studio
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and studio sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit introduces students to the key principles which underlie the analysis and design of information systems to support business and other organisational undertakings. It covers design and design thinking, requirements elicitation, consulting skills and conceptual and logical systems modelling.

On successful completion of this unit, students should be able to:

1. select and use conceptual and logical modelling techniques to design an information system;
2. select and use techniques to elicit requirements for an information system design;
3. select and use approaches to the systems development lifecycle including the waterfall model and modern alternatives;
4. assess and discuss the capabilities and limitations of an information system;
5. communicate the requirements for the business functionality of an information system in terms of data required, data storage and processing to technical and non-technical stakeholders.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour studio
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and studio sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit aims to provide students with the basic concepts involved in the development of well structured software using a programming language. It concentrates on the development of problem solving skills applicable to all stages of the development process. Students gain experience with the translation of a problem specification into a program design, and the implementation of that design into a programming language. The unit introduces software engineering topics such as maintainability, readability, testing, documentation, modularisation, and reasoning about correctness of programs. Students are expected to read and understand existing code as well as develop new code.

On successful completion of this unit, students should be able to:

1. design, construct, test and document small computer programs using Java;
2. interpret and demonstrate software engineering principles of maintainability, readability, and modularisation;
3. explain and apply the concepts of the "object-oriented" style of programming.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour laboratory
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit will introduce the concept of data management in an organisation through relational database technology. Theoretical foundation of relational model, analysis and design, implementation of relational database using SQL will be covered.

At the completion of this unit, students should be able to:

1. explain the motivations behind the development of database management systems;
2. describe the underlying theoretical basis of the relational database model and apply the theories into practice;
3. evaluate several design options and construct a database design;
4. develop a database based on a sound database design;
5. construct queries that meet user requirements;
6. contrast the differences between non-relational database models and the relational database model.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

For Monash Online: In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • 2 hours of lectures
   • One 2-hour laboratory.
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lecture and lab sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.
3. Contact hours for Monash ONLINE students:
   • Two hours/week online group sessions
   • Online students generally do not attend lecture, tutorial and lab sessions, however should plan to spend equivalent time working through resources and participating in discussions.
4. Additional requirements (all students):
   • A minimum of 8 hours independent study per week (22 hours per week for Monash Online students) for completing lab and project work, private study and revision.

See also Unit timetable information

This unit introduces programming fundamentals and the Python language to students. The unit provides a foundational understanding of program design and implementation of algorithms to solve computational problems. Fundamental programming control structures, built in and complex data types and mechanisms for modularity will be presented in Python.

Topics covered will include basic input and output, program control structures, basic data structures and modular program structures, problem solving strategies and techniques for algorithm development, iteration and recursion.

Upon successful completion of this unit, students should be able to:

1. design, construct, test and document computer programs using Python;
2. recognise the relationship between a problem description and program design;
3. demonstrate how basic data structures and data types function;
4. investigate different strategies for algorithm development and evaluate these to select an appropriate solution to a given problem.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

For on-campus: Examination (2 hours): 50%; In-semester assessment: 50%

Monash Online: In-semester assessment: 100%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures
   • Two hours/week laboratories
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions

   Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.

3. Additional requirements (all students):
   • A minimum of 8 hours per week of personal study (22 hours per week for Monash Online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

This unit introduces students to the fundamentals of computer systems and the computing environment, using Linux as a case study of a modern operating system. Topics covered include: CPU, memory, storage devices, peripheral hardware, networking fundamentals, operating systems fundamentals, practical Linux considerations including Desktop and Enterprise applications, file systems, shell scripting, client/server applications and system administration.

On completion of this unit, students should be able to:

1. examine and describe computer hardware and software architectures;
2. explain the three major functions of an operating system (OS), namely, process management, memory management, and file management;
3. explain network technologies;
4. write Unix commands for file management;
5. apply Unix commands to interact with OS;
6. develop Unix shell scripts;
7. manage usage and administration of Linux systems; and
8. deploy Linux in personal and enterprise contexts.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • One 1-hour lecture
   • One 3-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

The unit will introduce students to fundamentals of data and computer communications methods and techniques. It covers: ISO and TCP/IP layered protocols; physical layer concepts: data transmission methods, signal encoding and digital data communication techniques; data link control protocol, multiplexing methods; WAN and LAN networking fundamentals; internetworking and transport protocols; and basic concepts of network security.

At the completion of this unit students should be able to:

1. describe the underlying fundamental theories and models of transmitting data across a communication channel;
2. identify and describe the concepts and theories of standard network protocols;
3. describe the functions and architectures of local area networks, wide area networks and the Internet;
4. identify and describe fundamental concepts of network security including common threats and countermeasures;
5. evaluate several different design options and formulate a simple network design.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Mathematical topics fundamental to computing and statistics including trees and other graphs, counting in combinatorics, principles of elementary probability theory, linear algebra, and fundamental concepts of calculus in one and several variables.

Upon successful completion of this unit, students should be able to:

1. use trees and graphs to solve problems in computer science;
2. apply counting principles in combinatorics;
3. describe the principles of elementary probability theory, evaluate conditional probabilities and use Bayes' Theorem;
4. demonstrate basic knowledge and skills of linear algebra, including the manipulation of matrices, solution of linear systems, and evaluate and apply determinants;
5. explain fundamental concepts in calculus including basic differentiation and integration, and composite, inverse and parametric functions;
6. perform key skills in the calculus of functions of several variables including the calculation of partial derivatives, find tangent planes and identify stationary points, root findings and convexity for optimisation.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 3 hours and 10 minutes.

On-campus: Examination (3 hours): 60%; In-semester assessment: 40%

Monash Online: In-semester assessment: 100%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Three hours/week lectures
   • One and half hours/week laboratories
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions

   Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.

3. Additional requirements:
   • A minimum of 7.5 hours per week of personal study (22 hours per week for Monash online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

This unit will examine ICT and the hardware infrastructure that underpins secure delivery of the software applications and the robustness required to deliver modern health services. Picture Archive and Communication Systems (PACS) and Radiology Information Systems (RIS) are two health applications to be covered more in depth, together with an overview of other health related software applications such as the Electronic Patient Record (EPR). Students will also explore project and change management principles and learn how they can be applied more specifically to advanced medical radiation practice.

Upon successful completion of this unit, students should be able to:

1. Describe their obligations in relation to Patient Health Record Privacy and Security.
2. Explain how knowledge of ICT terminology and practices facilitates more effective outcomes for users of health services.
3. Distinguish between the various components of the IT infrastructure including Network, Virtual Server environment and ICT support mechanisms.
4. Critically evaluate the roles and interdependencies of the software applications of PACS and RIS, and their relationship with other health IT applications.
5. Apply the principles of Project Management and Change Management methodologies in their work.
6. Demonstrate how health informatics functions across the wider health domain and how integration is applied.
7. Create Business Continuity Plans and Disaster Recovery Plans for their Health IT applications.

• 3 x Medical imaging data management case based assignments (30% each). The deliverables incorporates 1,500 words report for each and a 200 words reflection exercise (10% of the assessment).
• 2 x Online quizzes (10%)

Off-campus: 6 hours per week of direct engagement in the learning materials and 6 hours of self-directed study for 12 weeks.

See also Unit timetable information

Radiography and medical imaging