Program Requirements

The Master of Machine Learning and Computer Vision requires the completion of 96 units.

A minimum of 24 units must come from completion of 8000-level courses.

The 96 units must consist of:

6 units from completion of a programming course from the following list:

COMP6710 - Structured Programming

COMP6730 - Programming for Scientists

6 units from completion of a professional practice course from the following list:

COMP6250 - Professional Practice 1

COMP8260 - Professional Practice 2

          24 units from completion of courses from the following list:

COMP6528 - Computer Vision

COMP8539 - Advanced Topics in Computer Vision

COMP6670 - Introduction to Machine Learning

COMP8600 - Statistical Machine Learning

COMP8650 - Advanced Topics in Machine Learning

COMP8536 - Advanced Topics in Deep Learning for Computer Vision

A further 24 units from completion of Computer Vision and Machine Learning courses in the following list:

COMP6262 - Logic

COMP6320 - Artificial Intelligence

COMP6490 - Document Analysis

COMP8620 - Advanced Topics in Artificial Intelligence

COMP8691 - Optimisation

ENGN6627 - Robotics

COMP6261 - Information Theory

COMP8535 - Engineering Data Analytics

COMP6461 - Computer Graphics

COMP6528 - Computer Vision

COMP8539 - Advanced Topics in Computer Vision

COMP6670 - Introduction to Machine Learning

COMP8600 - Statistical Machine Learning

COMP8650 - Advanced Topics in Machine Learning

COMP8536 - Advanced Topics in Deep Learning for Computer Vision

12 units from completion of a research project or industry internship in the following list*:

COMP8715 - Computing Project

COMP8830 - Computing Internship

or an alternative university independent study course (under COMP8603 - Research Project for 24 units) with permission of the Program Convenor.

*An extended research project of maximum 24 units of credits may be taken with GPA requirement, with the additional units counting toward the 24u of program electives. 

24 units of elective courses offered by the ANU. 

Admission Requirements

Applicants must present one of the following:

• A Bachelor degree or international equivalent in a cognate disciplines with a GPA of 5/7
• A Bachelor degree or international equivalent in a cognate discipline with a GPA of 4/7 and a minimum of three years relevant work experience

The GPA for a Bachelor program will be calculated from (i) a completed Bachelor degree using all grades and/or (ii) a completed Bachelor degree using all grades other than those from the last semester (or equivalent study period) of the Bachelor degree. The higher of the two calculations will be used as the basis for admission.

Cognate Disciplines: Electrical and/or Electronics engineering, Computer Science, Software Engineering, Computer Engineering, Automation, Mechatronics, Telecommunications, Mathematics, Physics, Bioinformatics, Control systems and engineering, Statistics, Artificial Intelligence, Biomedical Science, Optical Engineering.

Ranking and English language proficiency: At a minimum, all applicants must meet program-specific academic/non-academic requirements, and English language requirements. Admission to most ANU programs is on a competitive basis. Therefore, meeting all admission requirements does not automatically guarantee entry. In line with the University's admissions policy and strategic plan, an assessment for admission may include competitively ranking applicants on the basis of specific academic achievement, English language proficiency and diversity factors. Applicants will first be ranked on a GPA ('GPA1') that is calculated using all but the last semester (or equivalent) of the Bachelor degree used for admission purposes. If required, ranking may further be confirmed on the basis of:

• a GPA ('GPA2') calculated on the penultimate and antepenultimate semesters (or equivalent) of the Bachelor degree used for admission purposes; and/or
• demonstrating higher-level English language proficiency

Prior to enrolment in this ANU program, all students who gain entry will have their Bachelor degree reassessed, to confirm minimum requirements were met.

Further information: English language admission requirements and post-admission support

Diversity factors: As Australia’s national university, ANU is global representative of Australian research and education. ANU endeavours to recruit and maintain a diverse and deliberate student cohort representative not only of Australia, but the world. In order to achieve these outcomes, competitive ranking of applicants may be adjusted to ensure access to ANU is a reality for brilliant students from countries across the globe.

Assessment of qualifications: Unless otherwise indicated, ANU will accept all Australian Qualifications Framework (AQF) qualifications or international equivalents that meet or exceed the published admission requirements of our programs, provided all other admission requirements are also met.

Where an applicant has more than one completed tertiary qualification, ANU will base assessment on the qualification that best meets the admission requirements for the program. Find out more about the Australian Qualifications Framework: www.aqf.edu.au.

Unless otherwise indicated, where an applicant has more than one completed tertiary qualification, ANU will calculate the GPA for each qualification separately. ANU will base assessment on the best GPA of all completed tertiary qualifications of the same level or higher.

ANU uses a 7-point Grade Point Average (GPA) scale. All qualifications submitted for admission at ANU will be converted to this common scale, which will determine if an applicant meets our published admission requirements. Find out more about how a 7-point GPA is calculated for Australian universities: www.uac.edu.au/future-applicants/admission-criteria/tertiary-qualifications.

Fee Information

All students are required to pay the Services and amenities fee (SA Fee)

The annual indicative fee provides an estimate of the program tuition fees for international students and domestic students (where applicable). The annual indicative fee for a program is based on the standard full-time enrolment load of 48 units per year (unless the program duration is less than 48 units). Fees for courses vary by discipline meaning that the fees for a program can vary depending on the courses selected. Course fees are reviewed on an annual basis and typically will increase from year to year. The tuition fees payable are dependent on the year of commencement and the courses selected and are subject to increase during the period of study.

For further information on Fees and Payment please see: https://www.anu.edu.au/students/program-administration/fees-payments

Scholarships

ANU offers a wide range of scholarships to students to assist with the cost of their studies.

Eligibility to apply for ANU scholarships varies depending on the specifics of the scholarship and can be categorised by the type of student you are.  Specific scholarship application process information is included in the relevant scholarship listing.

For further information see the Scholarships website.

Learning Outcomes

1. Propose and develop novel solutions based on current research literature and state-of-the-art computer vision techniques. 

2. Research and apply development tools for solving computer vision and machine learning problems.

3. Interpret and present the methodologies and implementation details?relevant to computer vision and machine learning technologies?with audience-?tailored communications.

4. Conduct Machine Learning and/or Computer Vision research (applied or pure) project workflows consistent with current practice.

5. Synthesize advanced knowledge, techniques and tools for computer vision and machine learning applications. 

Inherent Requirements

Information on inherent requirement is currently not available for this program.