Master of Information Technology Specialisation in Artificial Intelligence

Dropdown Menu with Submenu and Custom Arrows
Course Overview

The Artificial Intelligence (AI) specialisation within the Master of Information Technology (MIT) offers students the opportunity to develop expertise in one of the most dynamic and impactful areas of computing today. Designed for graduates from both IT and non-IT backgrounds, the program provides a broad IT foundation before enabling students to specialise in the theories, tools, and applications of AI.

The curriculum covers a wide spectrum of AI concepts, from machine learning and deep learning through to natural language processing, and ethical AI. Students develop the ability to design, train, and evaluate intelligent systems, and critically assess the implications of AI in industry, society, and research. Practical learning is a core feature, with students engaging in lab-based projects, case studies, and applied research. The Applied Project provides students the opportunity to work on complex AI solutions for real-world problems, demonstrating innovation, technical proficiency, and ethical awareness to prospective employers.

As global demand for AI expertise continues to expand, this specialisation positions graduates for different AI careers to apply AI solutions across a wide range of industries.

Course Structure

To qualify for the award, students are required to successfully complete the seven (7) core units listed below, plus three (3) specialisation units, plus two (2) electives from the provided options. This totals to 12 units which is equivalent to 96 credit points.

Unit Code and TitleCredit Points*Pre-requisite(s)
ICT5150 Information Systems8Nil
ICT5151 Data and Information Management8Nil
ICT5152 Software and Systems Design8Nil
ICT5201 Research Methods and Data Analysis8

24 Credit Points

ICT5250 Computer Networks and Security8ICT5150 Information Systems
PRJ5003 Project Constraint Management8Nil
ICT6001 Applied Project8ICT5201 Research Methods and Data Analysis

*A unit worth 8 credit points is equal to 0.167 Equivalent Full-Time Student Load (EFTSL).

Unit Code and TitleCredit Points*Pre-requisite(s)
ICT5356 Principles of Artificial Intelligence^8ICT5150 Information Systems
ICT5357 Problem-solving and Decision-Making with Machine Learning^8ICT5356 Principles of Artificial Intelligence
ICT5358 Unleashing the Power of Generative AI Models^8

ICT5152 Software and Systems Design

ICT5356 Principles of Artificial Intelligence

*A unit worth 8 credit points is equal to 0.167 Equivalent Full-Time Student Load (EFTSL).

Select one (1) ICT elective of choice denoted by (^), plus one (1) other elective of choice.

Unit Code and TitleCredit Points*Pre-requisite(s)
ICT5253 Cloud Architectures and Solutions^8

ICT5150 Information Systems

ICT5151 Data and Information Management

ICT5350 Securing IT Systems^8ICT5250 Computer Networks and Security
ICT5351 Cyber Defence^8ICT5250 Computer Networks and Security
ICT5352 Cyber Security Management^8ICT5250 Computer Networks and Security
ICT5354 Enterprise Network Design^8ICT5250 Computer Networks and Security
ICT5355 Emerging Network Technologies^8ICT5250 Computer Networks and Security
PRJ5001 Project Management Profession8Nil
PRJ5002 Enterprise and Resource Planning8Nil
PRJ5004 Procurement, Quality and Risk Management8Nil
BUS5001 Ethical Legal and Industrial Frameworks8Nil
BUS5005 Digital Transformation in Business8Nil
BUS6003 Business Law8Nil
BUS6005 International Business8Nil

*A unit worth 8 credit points is equal to 0.167 Equivalent Full-Time Student Load (EFTSL).

Admission Requirements

The following academic admission criteria apply to all applicants to courses at APIC that lead to the award of an AQF Level 9 qualification. Additional English language requirements for international students are provided in the next tab.

Admission will be granted to applicants who meet any ONE of the following criteria:

  • Successfully completed a Bachelor’s degree (AQF 7) or higher, awarded by a recognised university or higher education institution or its international equivalent, in any discipline; OR
  • Applicants who have completed a postgraduate preparation program.

For more information on admission requirements including special entry requirements, please refer to the APIC Admission Policy.

All applicants from a non-English speaking background applying to a Master or Graduate Diploma course at APIC must satisfy ONE of the following English language requirements:  

  • IELTS Academic: overall band score of 6.5 or higher, with a minimum score of 6.0 in writing and speaking; OR
  • IBT (Internet-based TOEFL): Overall score of 79 with a writing section minimum of 21 and speaking 18; OR
  • Cambridge Certificate of Proficiency in English (CPE): Overall score 180, writing and speaking 180; OR
  • Cambridge Certificate of Advanced English (CAE): Overall 176 with a writing and speaking minimum score of 169: OR
  • PTE Academic Module with a minimum score of 58 with a writing and speaking section minimum of 50.

FEE-HELP is a Commonwealth Government loan available to eligible students enrolled in APIC Courses in order to help pay all or part of their tuition fees. 

FEE-HELP is available for all Units of Study for eligible students.

Details about HELP loans including eligibility requirements and repayment of a HELP debt can be foundhere.

The current FEE-HELP Information Booklet can be downloaded here.

If you have any questions about applying for FEE-HELP please contact us at:[email protected] 

Course Learning Outcomes

Graduates of MIT will be able to:

  • Master the core body of information technology knowledge.
  • Articulate project and IT systems management issues and principles.
  • Appraise current and emerging approaches and technologies in information technology.
  • Integrate ethical considerations into IT solutions and professional practices.
  • Communicate complex information technology concepts and solutions to specialists, non-specialists, and collaborators.
  • Create justifiable innovative solutions to complex information technology problems through independent research, industry standard technologies and methodologies.
Accreditation
  • APIC courses are nationally accredited and registered by the Tertiary Education Quality and Standards
    Agency (TEQSA) and included in the National Register of Higher Education Providers.
  • APIC is registered on the Commonwealth Register of Institutions and Courses for Overseas Students
    (CRICOS). MIT CRICOS Code is 108729F.
Skill Development
  • Build and train machine learning models
  • Apply deep learning with CNNs and RNNs
  • Develop natural language processing
  • Use AutoML and data-driven forecasting tools
  • Design and test generative AI applications
  • Apply prompt engineering
  • Evaluate ethical and social impacts of AI
Career Outcomes

Possible employment: 

  • Data Scientist
  • AI Research Scientist
  • AI/Machine Learning Engineer
  • AI Consultant
  • AI Engineer
  • Machine Learning Specialist
  • Data Scientist
  • Natural Language Processing (NLP) Engineer
  • Business Intelligence Analyst
  • AI Solutions Architect
  • Research and Development Specialist
Free
Duration 2 Years Full-Time
(104 Weeks)
Intakes Feb, Jun, Sep
CRICOS 108729F
Subjects 12
Locations SYD | MEL | BNE
Fees Click Here
Scholarships Available Click Here