Master of Science in Machine Learning
About This Programme
A 30-credit master's in advanced AI and machine learning, deep learning, computer vision, NLP, data mining and ML hardware, with course-only and thesis pathways. Prepares graduates for advanced machine-learning careers or doctoral study.
Course Highlights
- Dedicated machine-learning master's from the Department of Computer Science and Engineering
- Core in Advanced Artificial Intelligence and Advanced Machine Learning
- Core electives on generative/deep learning, advanced computer vision, NLP, data mining and cognitive robotics
- Breadth electives connect ML to cloud, cybersecurity, imaging and software engineering
What You'll Study
Thesis option (6 core + 9 core-elective + 6 breadth-elective credits + 9-credit thesis) or course option (6 core + 15 core-elective + 9 breadth-elective credits); seminar (MLR 695).
Required Core Courses (6 credits + 0-credit seminar)
- MLR 555 Advanced Artificial Intelligence3 credits
- MLR 570 Advanced Machine Learning3 credits
- MLR 695 Seminar0 credits
Core Elective Courses (9 credits thesis / 15 credits course option)
- MLR 503 Data Mining and Knowledge Discovery3 credits
- MLR 506 Hardware Architectures for Machine Learning3 credits
- MLR 508 Cognitive Robotics3 credits
- MLR 510 Generative Deep Learning3 credits
- MLR 511 Mobile Application Development with Machine Learning3 credits
- MLR 512 Advanced Computer Vision3 credits
- MLR 513 Advanced Natural Language Processing3 credits
- MLR 694 Special Topics in Machine Learning3 credits
Breadth Elective Courses (6 credits thesis / 9 credits course option)
- BME 543 Biomedical Imaging Technologies3 credits
- BME 581 Biomedical Informatics3 credits
- COE 505 Cloud Computing Infrastructure3 credits
- COE 545 Modeling and Testing in Software Engineering3 credits
- COE 555 Cyber Security3 credits
Thesis (thesis option only)
- MLR 699 Master's Thesis9 credits
Entry Requirements
MBA and MBDA applicants take the GMAT or the AUS admission test; a statement of purpose is required for some programmes.
Careers
Machine-learning and AI engineering and data-science roles across technology, finance, healthcare and government, plus doctoral study.
Accreditation & Professional Recognition
Licensed/accredited by the UAE Commission for Academic Accreditation (CAA), Ministry of Higher Education and Scientific Research; AUS is institutionally US-accredited by MSCHE (Middle States).
Programme Details
Award
Master of Science in Machine Learning
Start Date
August 2026 (Fall; Spring intake for many programmes)
Typical Offer
BS in Computer Science or Computer Engineering with strong programming competency, CGPA 3.0/4.0, plus IELTS 6.5 (or TOEFL iBT 80). Related engineering/quantitative-science degrees considered case-by-case.
Duration
2 years
Qualification
Masters
Subject Area
Computer Science
Campus
Sharjah
Course Type
Master of Science
Study Pattern
Full time
Delivery Format
In person
Tuition Fee
AED 82,200/yr
Apply online at apply.aus.edu with transcripts, a CV, references and a statement of purpose where required. The graduate application fee is AED 450 + 5% VAT. AUS offers graduate assistantships to qualified applicants.