single degree

Graduate Certificate of Machine Learning and Computer Vision

A single graduate award offered by the ANU College of Engineering and Computer Science

  • Minimum 24 Units
  • Mode of delivery
    • Online
  • Field of Education
    • Computer Science
  • Academic contact
  • Minimum 24 Units
  • Mode of delivery
    • Online
  • Field of Education
    • Computer Science
  • Academic contact

Program Requirements

The Graduate Certificate of Machine Learning and Computer Vision requires the completion of 24 units, which must consist of:

COMP6730 Programming for Scientists

COMP6670 Introduction to Machine Learning

ENGN6528 Computer Vision

ENGN6627 Robotics

Admission Requirements

NOTE: The program is not taking applications for 2022

This program is only open to Domestic students

A Bachelor degree or international equivalent with a minimum GPA of 4.0 / 7.0 in a cognate discipline.

All applicants must meet the University’s English Language Admission Requirements for Students

Credit Granted

Credit for this program is not available.

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.

Annual indicative fee for domestic students

For more information see:

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:


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.

NOTE: The program is not taking applications for 2023

Rapid societal changes are being driven by the increasing ubiquity of AI and automation. Cornerstone technologies in these fields are Machine Learning and Computer Vision. This program provides students with specific expertise and knowledge in machine learning, computer vision, and robotics. For interested students, this program provides a pathway to complete the Master of Machine Learning and Computer Vision.

The Graduate Certificate of Machine Learning and Computer Vision comprises the equivalent of 0.5 years of full-time study. The program is taught online in intensive blended mode. Students are expected to be enrolled part-time and can complete the program in 1 year of part time study.


This program is available to domestic students only.

Career Options

ANU ranks among the world's very finest universities. Our nearly 100,000 alumni include political, business, government, and academic leaders around the world.

We have graduated remarkable people from every part of our continent, our region and all walks of life.

This program is available for applications until second semester, 2022

Learning Outcomes

  1. Understand computer vision and visual perception problems.

  2. Be proficient in using development tools for solving computer vision and machine learning problems

  3. Present the methodologies and implementation details of an implementation in a concise and clear manner

  4. Apply learned knowledge, techniques and tools to robotics applications

Inherent Requirements

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

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