Master of Information Technology,
Specialisation in Artificial Intelligence

CRICOS Course Code: 117490E

The Master of Information Technology (MIT) and its specialisation in Artificial Intelligence (AI) will allow graduates to upskill and transition to new and emerging roles or refresh and augment existing competencies and skills. Employment opportunities for graduates of the MIT are wide-ranging because digital skills, including AI, are inherent in most jobs. Therefore, organisations will compete for graduates with highly-valued IT knowledge, competencies and skills.

Careers in traditional technology industries, including software, aerospace, and defence, are in high demand. Increasingly, IT skills are sought after in consulting, medical / pharmaceutical and banking / finance industries. Other industries include hospitality / travel, consumer products, and manufacturing.

The course is a 2-year full-time or equivalent part-time course comprised of 16 subjects. The course contains 13 core subjects and the choice of 3 electives which are undertaken in the final year of study.

AQF level : 9

SHEA’s partnership with the Australian Computer Society (ACS) allows each student free membership to ACS. Each student will have access to over 35000 learning resources, 400 professional events, the chance to be professionally mentored and access to insights into the tech industry.

Graduates of the Master of IT will be able to:
CLO1	Demonstrate in-depth and integrated knowledge of advanced IT concepts, systems, software, and associated standards, policies, and procedures.
CLO2	Design, recommend and justify solutions to solve complex IT-related problems to support the realisation of strategic objectives.
CLO3	Communicate effectively with technical and non-technical stakeholders in diverse work environments to meet IT needs and expectations.
CLO4	Critically appraise IT projects in awareness of legislative, cultural, and workplace health and safety requirements and responsibilities.
CLO5	Apply sustainable and ethical thinking across the broad and diverse spectrum of IT professional practice.
CLO6	Consolidate the integration of ICT standards and theory to achieve best practice outcomes as an IT practitioner.

The types of roles that are relevant to a MIT graduate with a specialisation in AI are evolving to reflect the needs of each business and industry. Potential employment opportunities include:

AI Engineer
Machine Learning (ML) Engineer
Data Engineer
Software Engineer
Natural Language Processing (NLP) Engineer
Robotics Engineer
Deep Learning Engineer

The mode of delivery is face-to-face, supported by SHEA’s Learning Management System for access to subject-specific learning resources and information, including submitting assessments. Moodle will be the LMS for delivering the learning strategy to engage interactively with students using the digital tools anytime and anywhere to augment their classroom experience.
The assessment types in the course are predominantly authentic assessments with some traditional assessments for knowledge-based subjects in the first year:

Problem-based tasks (either individually or team)
Case studies
Presentations
Report
Peer and self-assessment (moderated)
Quizzes (used well can keep students engaged, formative assessment because quizzes are easy to administer and provide feedback)
Project (individual and in teams)

Subject code and title		Core/Elective
ITOP801	Concepts in Information Systems	Core 1
PROF802	Ethics, Bias, and the IT Professional	Core 2
SCTY803	Cybersecurity Management	Core 3
DATM804	Database Systems	Core 4
PROF805	Design Thinking for IT	Core 5
DATM806	Cloud Computing	Core 6
PROF807	IT Governance and Risk Management	Core 7
PROG808	Artificial Intelligence Fundamentals	Core 8
SCTY901	Data Security and Privacy	Core 9
	Elective 1 (Refer to Table below)	Elective 1
	Elective 2 (Refer to Table below)	Elective 2
	Elective 3 (Refer to Table below)	Elective 3
PRMG903	IT Project Risk Management	Core 10
PROF909	Information Technology Project Part A (Literature Review, Project Selection, Planning)	Core 11
SCTY904	Cyber Security and Networking	Core 12
PROF910	Information Technology Project Part B (Final Report and Applied Work)	Core13
AI Specialisation: Choose 3 Elective Options
PROG930	Adversarial Machine Learning	AI Elective
PROG931	Advanced Topics in Artificial Intelligence	AI Elective
PROG932	Natural Language Processing and Generative AI	AI Elective
PROG933	Data and AI Ethics	AI Elective

ADMISSION REQUIREMENTS

Mode of Delivery

On Campus

We focus on learning and teaching delivery method where students will be required to engage in the subject content prior to classes and tutorials so that the face-to-face engagement can be used to develop higher-order skills such as interpersonal skills and teamwork.

On campus
A mix of online tools through the Learning Management System to subject-specific learning resources and information including submitting assessments
Out-of-class activities to engage students throughout their course.

CREDIT FOR PRIOR LEARNING

Skyline Higher Education Australia (SHEA) grants credit towards a course of study on the basis of prior learning, whether from formal studies or professional work experience to ensure that students commence study at a level appropriate to their prior learning experiences so that they are not required to repeat prior learning. For more information please visit SHEA’s Credit For Prior Learning Policy.