Technology

Master of Artificial Intelligence and Machine Learning

  • Domestic
  • International
  • Duration

    2 years full-time or part-time equiv.
  • Start Dates

    January, May and September
  • Location

    North Terrace Campus
  • Duration

    2 years full-time or part-time equiv.
  • Start Dates

    January, May and September
  • Location

    North Terrace Campus

About Degree

Harness AI to shape the future

Artificial intelligence and machine learning make life easier, in all its aspects: healthcare, defence, entertainment, agriculture. Artificial intelligence and machine learning now present the world’s single greatest commercial opportunity. Research indicates that by 2030 it could increase global GDP by up to 14%—a staggering US$15.7 trillion gain. Locally, hundreds of millions are invested towards industry-wide transformation, promoting significant job market growth.

Employment prospects are outstanding. AI and machine learning appointments worldwide have doubled in the past three years, with demand easily outstripping supply.

The Master of Artificial Intelligence and Machine Learning, conducted through the University of APSB’s world-renowned Australian Institute for Machine Learning (AIML), will position you perfectly to play a senior leadership role in this exciting future.

What will you do?

Our Master of Artificial Intelligence and Machine Learning is driven by AIML’s cutting-edge research and extensive industry links, spanning diverse international sectors – from health, medical technology, defence and security to environment and natural resources.

This degree will equip you with:

  • highly advanced technical skills in machine learning and AI application development, including in specialist areas, such as deep learning and visual question answering
  • a firm grasp of the commercial, organisational and research opportunities presented by machine learning and AI
  • a deep understanding of the disciplines’ ethical and social considerations
  • the chance to gain invaluable real-world experience, through a major research or industry-based project as well as an optional industry internship.
  • extensive industry connections and networks.

You’ll also receive ongoing mentoring, feedback and direction from AIML’s world-class researchers and high-performing industry professionals.

How will you study?

This program is able to be studied in either part-time, standard full-time or accelerated mode—enabling you to undertake your studies at a pace and level of commitment that suits you. For further information, see the Degree Structure section.

Where could a Master of Artificial Intelligence and Machine Learning take you?

You could enhance children’s education with AI-based personal study plans. You might help climate-change-affected farmers feed the world with machine-learning-driven environmental management systems. Perhaps you’ll help extend life expectancy by perfecting tailored health-plan development based on AI analysis of key predictive data.

The degree also provides an outstanding foundation for further advanced study through a machine learning or AI PhD.


Entry Requirements

Choose your applicant type to view the relevant admissions information for this program.I am a:

  • Domestic
  • International

    Domestic applicants

    SATAC Code3CM216, 3CM248
    DefermentYes - 2 year
    IntakeJanuary, May and September
    PrerequisitesSACE Stage 2: Mathematical Methods . IB: Mathematics: Applications and Interpretations (HL) or Mathematics: Analysis and Approaches (SL)

    MathTrackX is an online bridging program available as a recognised alternative to Mathematical Methods.
    Selection Criteria
    Graduate entry


    Higher Education StudyA completed Bachelor degree and a minimum GPA of 4.5.


    Student Profile
    Applicant backgroundSemester one/Full year intake 2022
    Number of studentsPercentage of all students
    International students2288.0%
    All students25100.0%


    International applicants

    CRICOS107539J
    IntakeJanuary, May and September
    Australian Year 12SACE Stage 2: Mathematical Methods . IB: Mathematics: Applications and Interpretations (HL) or Mathematics: Analysis and Approaches (SL)

    MathTrackX is an online bridging program available as a recognised alternative to Mathematical Methods.
    International QualificationsMathematics
    Selection Criteria
    English Language Requirements

    Australian Year 12Successful completion of an Australian year 12 qualification with a minimum pass in an accepted English language subject
    English Tests accepted by the University of APSB
    IELTSOverall 6.5Reading 6Listening 6Speaking 6Writing 6





    TOEFLOverall 79Reading 13Listening 13Speaking 18Writing 21





    PearsonOverall 58Reading 50Listening 50Speaking 50Writing 50





    C1 AdvancedOverall 176Reading 169Listening 169Speaking 169Writing 169





    Qualifications that meet minimum English requirementsA range of alternative qualifications may meet the University’s minimum English requirements
    Academic Entry Requirements

    Detailed information on international qualifications assessment

    Tertiary QualificationsBachelor degree or equivalent with a GPA of 4.5
    How to Apply
    Application information for international students
    Important application deadlines for international students

    Student Profile
    Applicant backgroundSemester one/Full year intake 2022
    Number of studentsPercentage of all students
    International students2288.0%
    All students25100.0%


Fees and Scholarships

Choose your applicant type to view the relevant fees and scholarships information for this program.I am a:

  • Domestic
  • International

    Domestic applicants

    Indicative annual tuition fees
    Australian Full-fee place: $41,000

    Where the standard duration of the program is less than one year the full cost of the program is displayed.

    Scholarships

    These scholarships, as well as many others funded by industry and non-profit organisations, are available to potential and currently enrolled students.


    International applicants

    Indicative annual tuition fees (24 units)International student place: $48,500

    Where the standard duration of the program is less than one year the full cost of the program is displayed.

    More information on International Student tuition fees.

    Scholarships

    These scholarships, as well as many others funded by industry and non-profit organisations, are available to potential and currently enrolled students.


Careers

Potential careers

Computational Scientist, Computer Programmer, Computer Scientist, Digital Strategist, Software Specialist, IT Manager, IT Programmer, Diagnostic Technician


Degree Structure

The Master of Artificial Intelligence and Machine Learning is ideal for students who have a background/qualifications in any professional field and are looking to upskill in this exciting, high-demand area. The curriculum has been designed to include all of the necessary computer science foundations for students to succeed. Students with relevant qualifications or experience can apply for advanced standing*.

To qualify for the Master of Artificial Intelligence and Machine Learning, students must satisfactorily complete a program of study consisting of the following requirements with a combined total of no less than 48 units comprising:

  • Four core courses to the value of 12 units
  • Up to five** elective set A courses to the value of 15 units
  • Three courses from elective set B to the value of 9 units
  • Two project courses from either the Research Pathway or Industry Pathway to the value of 12 units

*For further information, please contact one of our friendly program advisors.

**Unless exempted international students are required to take ENG 7057 Communication & Critical Thinking in lieu of an elective.


Study mode
This program is able to be studied in either part-time, standard full-time or accelerated mode—enabling you to undertake your studies at a pace and level of commitment that suits you*.

  • Accelerated mode – 12 units (4 courses) per trimester
  • Standard full-time mode – 24 units (8 courses) per year
  • Part-time mode – 3 or 6 units (1 or 2 courses) per trimester
You can even choose the study load that works best for you at different times of the year.

Whatever mode you choose, our interactive blend of online and face-to-face learning supports you in fitting your study around other commitments—without compromising on authentic and immersive learning experiences.

*International students please note: accelerated study modes are subject to visa conditions. Please contact one of our friendly program advisors for more information.

Example Study Plan

Core course (12 units total)
Students must complete all of the following

  • COMP SCI 7210  Foundations of Computer Science A
  • COMP SCI 7211  Foundations of Computer Science B
  • COMP SCI 7327  Concepts in Artificial Intelligence and Machine Learning
  • MATHS 7027  Mathematical Foundations of Data Science
Elective Set A (15 units total)

Option 1:
5 courses* (3 units each)

OR

Option 2:
3 courses* (3 units each) plus ENG 7111  Internship (6 units)


  • COMP SCI 7212  Human and Ethical Factors in Computer Science
  • COMP SCI 7314  Introduction to Statistical Machine Learning
  • COMP SCI 7315  Computer Vision
  • COMP SCI 7317  Using Machine Learning Tools PG
  • COMP SCI 7318  Deep Learning Fundamentals
  • COMP SCI 7417  Applied Natural Language Processing
  • COMP SCI 7419  Deep Learning: Image Processing
  • ENG 7111  Internship (6 units)
  • PHIL 7005  Machine Learning and Artificial Intelligence
*Unless exempted international students are required to take ENG 7057  Communication & Critical Thinking in lieu of an elective.
Elective Set B (9 units total)
Students must choose 3 courses

  • COMP SCI 7209  Big Data Analysis and Project
  • COMP SCI 7306  Mining Big Data
  • MATHS 7103  Probability & Statistics PG
  • STATS 7107  Statistical Modelling and Inference
Project (12 units total)

Option 1:
Research Pathway

Option 2:
Industry Pathway

Research pathway

COMP SCI 7205A  Artificial Intelligence and Machine Learning Research Project Part A
COMP SCI 7205B  Artificial Intelligence and Machine Learning Research Project Part B
OR

Industry pathway
COMP SCI 7206A  Artificial Intelligence and Machine Learning Industry Project Part A
COMP SCI 7206B  Artificial Intelligence and Machine Learning Industry Project Part B


RECOGNITION AND AFFILIATIONS

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