Master of Machine Learning and Computer Vision
A two-year master’s programme at ANU combining advanced machine learning and computer vision for industry and academic careers.
Best for:Best for graduates with a strong background in computer science, engineering, or related disciplines seeking to specialise in machine learning and computer vision for careers in industry or academia.
Overview
The Master of Machine Learning and Computer Vision (MMLCV) at The Australian National University (ANU) is a two-year coursework programme designed to equip students with specialised knowledge and professional skills in machine learning and computer vision. Taught by leading researchers at the ANU College of Engineering & Computer Science, this programme leverages ANU’s affiliation with the ARC Centre of Excellence for Robotic Vision. It offers flexibility for careers in industry or academia, with potential progression to PhD study for high-performing students. The curriculum integrates theoretical foundations with practical applications, preparing graduates for roles in AI-driven fields.
What you'll do
- Complete a structured two-year coursework programme covering advanced topics in machine learning and computer vision.
- Engage in hands-on projects and research to apply theoretical knowledge to real-world problems.
- Develop professional skills for careers in AI-driven industries or further academic study.
- Participate in seminars and workshops led by prominent researchers in the field.
- Conduct an independent research project under faculty supervision, contributing to the field of robotic vision or related areas.
- Collaborate with peers and industry partners to solve complex challenges in AI and computer vision.
Requirements
Degree required: A Bachelor degree or international equivalent in a cognate discipline (e.g., Computer Science, Engineering, Mathematics, or related fields) with either: (1) a GPA of 5/7, or (2) a GPA of 4/7 and a minimum of three years of relevant work experience.
Language: English proficiency (if applicable to international students, though not explicitly stated in the source).
Instruction: English
- Strong academic background in computer science, engineering, or a related quantitative discipline.
- Proficiency in programming languages commonly used in machine learning (e.g., Python).
- Basic understanding of linear algebra, calculus, and statistics.
- Ability to work independently and collaboratively in a research-oriented environment.
- Open to domestic and international applicants.
- No age restrictions mentioned.
- No specific residency requirements mentioned.
Funding & terms
Programme and admissions
Admissions not verified
A catalogue listing does not mean applications are open or funding is guaranteed. Check the source for your intake.
- Intake
- Not confirmed by the source
- Duration
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- Teaching language
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- Taught / research mode
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- Study mode
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- Campus
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- Prerequisites
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- Application instructions
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- Tuition
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- Funding
- Not confirmed by the source
How to apply
Deadline: unknown (programme-based admissions; check ANU portal for specific intake dates)
Applicants must submit an online application through the ANU portal, including academic transcripts, a personal statement, and any additional documents required by the programme. International students may need to provide proof of English proficiency. The application process is handled directly through the ANU programmes and courses website.
- Academic transcripts (Bachelor’s degree and any higher education qualifications)
- Personal statement or research proposal (if applicable)
- Curriculum Vitae (CV)
- Proof of English proficiency (if applicable)
- Letters of recommendation (number not specified)
Contact
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.