Master of Machine Learning and Computer Vision Australian National University

Master of Machine Learning and Computer Vision (099247C) at Australian National University

Master of Machine Learning and Computer Vision (CRICOS course code 099247C) is a Masters Degree (Coursework) delivered by Australian National University over 2 years. This program is designed for students seeking advanced skills in computer vision and machine learning, two of the fastest-growing fields in technology. As a CRICOS-registered course (CRICOS 00120C), it meets Australian Government standards for international education. ANU, a Group of Eight university based in Canberra, offers world-class research and teaching facilities. Graduates are prepared for roles in AI, robotics, and data science. With over 1,500 CRICOS-registered providers in Australia, ANU stands out for its strong industry connections and Canberra's vibrant student community. Whether you're aiming for a career in tech or further research, this course provides a solid foundation.

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Data sourced directly from the official CRICOS register (April 2026)
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Course overview

Master of Machine Learning and Computer Vision (CRICOS course code 099247C) is a Masters Degree (Coursework) delivered by Australian National University over 2 years. This AQF Level 9 program falls under Field of Education 031305 - Computer Engineering. Students gain expertise in machine learning algorithms, deep learning, computer vision, and image processing. The course combines theoretical knowledge with practical applications, preparing graduates for high-demand roles in AI and technology sectors. As a CRICOS-registered course (provider CRICOS 00120C), it ensures quality education and student protections under the ESOS Act.

What you'll study

The field of Computer Engineering (031305) covers the design and development of computer systems, including hardware-software integration. At the Masters level, students typically study advanced topics such as neural networks, pattern recognition, and computer vision. Learning outcomes include the ability to design and implement machine learning solutions, analyse visual data, and apply ethical AI practices. While specific syllabi vary, graduates can expect to develop strong problem-solving and research skills. This knowledge is directly applicable to industries like autonomous vehicles, medical imaging, and robotics.

Duration and study mode

This course runs for 2 years (104 weeks on the CRICOS register), full-time. The language of instruction is English. It is a single qualification (no dual degree). No foundation studies are included. Students are expected to attend campus-based classes at ANU's Canberra City West location. The course is not available online or part-time for international students due to visa requirements. Full-time study ensures timely completion and compliance with Student visa (Subclass 500) conditions.

Fees

Indicative total tuition is A$113,760, with non-tuition fees of A$746, bringing the estimated total to A$114,506. These fees are sourced from the CRICOS register as at April 2026 and are set by Australian National University. Please note that Overseas Student Health Cover (OSHC), living costs, and the visa application charge are not included. For current fees, always check the provider's website at www.anu.edu.au. Fees are subject to change, and you should confirm them directly with ANU before applying.

Entry requirements

English language proficiency: IELTS 6.5-7.0 overall (or equivalent). Applicants are expected to hold a bachelor's degree in a related field (e.g., computer science, engineering, mathematics). Prior academic performance and relevant experience may be considered. No foundation or pathway options are listed for this course; however, ANU offers alternative pathways such as Graduate Certificates. Always verify specific entry requirements with ANU, as they can change. Meeting the minimum requirements does not guarantee admission.

Work component

No work component. This course does not include a mandatory work or internship component. However, international students on a Student visa (Subclass 500) are permitted to work 48 hours per fortnight during term and unlimited hours during scheduled breaks. Work can be casual or part-time, and Canberra offers opportunities in hospitality, retail, and research. Always check your visa conditions before starting work.

Delivery locations

Australian National University — Canberra City West, ACT. Canberra is Australia's capital city, with a population of around 450,000 and a large student population (over 40,000 at ANU alone). The city offers a high standard of living with public transport options including buses and light rail. Indicative weekly costs: rent A$300-500, groceries A$80-150, transport A$40-60. Canberra is known for its safety, culture, and outdoor activities. There are 1,556 CRICOS-registered providers across Australia, but only a few offer this specialised course.

Student visa

International students need a Student visa (Subclass 500) for this full-time course. Key requirements include: Genuine Temporary Entrant (GTE) criterion, Overseas Student Health Cover (OSHC), and proof of financial capacity (tuition + living expenses + travel). ESOS Act protections apply to all CRICOS-registered courses, ensuring education quality and student rights. Visa holders can work 48 hours per fortnight during term (since 2023). For visa guidance, consult the Department of Home Affairs or a registered MARA agent. HeadStart Academy does not provide immigration advice.

Is Canberra right for you?

Canberra offers a unique study experience: a planned city with excellent research institutions, government connections, and a high quality of life. As Australia's capital, it hosts national landmarks and a multicultural community. For tech students, Canberra has a growing AI and cybersecurity sector, with government and private sector research hubs. The climate features warm summers and cool winters. Public transport is reliable, and cycling is popular. Consider your preference for city life versus a more relaxed environment. Canberra's cost of living is moderate compared to Sydney or Melbourne.

How to apply

1. Research CRICOS-registered providers: Use HeadStart Academy to filter by course level (Masters Degree (Coursework)), field (Computer Engineering), and location (ACT). Confirm ANU's CRICOS registration (00120C) and the course code (099247C). 2. Apply directly to your chosen institution: Visit ANU's website, check entry requirements, prepare academic transcripts, English test scores (IELTS 6.5-7.0), and apply by the deadline. 3. Receive your Confirmation of Enrolment (CoE) and apply for your Student visa (Subclass 500): Once accepted, ANU issues a CoE. Use it to apply for a student visa online, paying close attention to GTE, OSHC, and financial evidence.

Start your application today. Research more CRICOS-registered courses on HeadStart Academy.

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Source-backed course facts

Master of Machine Learning and Computer Vision is a CRICOS-registered programme at Australian National University. Use this register extract [CRICOS register, Apr 2026] to cross-check codes, duration and indicative fees before you apply.

CRICOS register extract

Course
Master of Machine Learning and Computer Vision
CRICOS course code
099247C
Provider
Australian National University (00120C)
Course level
Masters Degree (Coursework)
Field of education
03 - Engineering and Related Technologies
Duration
104 weeks
Tuition (indicative)
A$113,760
Estimated total (indicative)
A$114,506
Delivery locations
Canberra City West
Work component
No

This page is general information only and not migration advice. Confirm Student visa (Subclass 500) requirements with the Department of Home Affairs.

Important notes for international students

  • Tuition and living-cost figures on this site are indicative only — confirm current fees with the provider before you accept an offer.
  • HeadStart Academy is not a registered migration agent and does not provide immigration advice. For Student visa (Subclass 500) rules, OSHC and financial capacity, verify with the Department of Home Affairs or a registered MARA agent.
  • Only CRICOS-registered providers may enrol overseas students. Always check the CRICOS course and provider codes on your offer and Confirmation of Enrolment (CoE).

Related pages

Frequently Asked Questions

The indicative tuition fee is A$113,760 for the full 2-year program, plus A$746 in non-tuition fees, totalling approximately A$114,506. These figures are from the CRICOS register (April 2026). Additional costs include OSHC (around A$600-800 per year), living expenses (A$21,041 per year as per Department of Home Affairs), and the visa application charge (currently A$1,600). Fees are set by ANU and subject to change.
The course duration is 2 years (104 weeks) full-time, as recorded on the CRICOS register. This is standard for a Masters Degree (Coursework) at AQF Level 9. International students must maintain full-time enrolment to comply with Student visa (Subclass 500) conditions. Part-time study is not permitted.
Applicants need an IELTS overall score of 6.5-7.0 (or equivalent) and a bachelor's degree in a related field such as computer science, engineering, or mathematics. ANU may consider relevant work experience or research background. Meeting minimum requirements does not guarantee admission. Always confirm with ANU for the most current prerequisites.
This course is delivered at Australian National University's campus in Canberra City West, ACT. Canberra is Australia's capital, with a strong research ecosystem and a community of over 40,000 students at ANU. The campus is accessible by public transport, and the city offers a safe, student-friendly environment with many part-time job opportunities.
CRICOS lists estimated total fees of A$114,506 for Master of Machine Learning and Computer Vision (tuition A$113,760). Figures are indicative as at the April 2026 register snapshot — confirm current fees with Australian National University before applying.
The CRICOS course code is 099247C, offered by Australian National University (provider code 00120C). Use these codes when checking your offer and CoE.