The scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. These algorithms are based on mathematical models learned automatically from data, thus allowing machines to intelligently interpret and analyze input data to derive useful knowledge and arrive at important conclusions. Machine learning is heavily used for enterprise applications (e.g., business intelligence and analytics), effective web search, robotics, smart cities, and understanding of the human genome.
Upon completion of the program requirements, the graduate will be able to:
The minimum degree requirements for the Master of Science in Machine Learning is 36 credits, distributed as follows:
Core courses | Number of courses | Credit hours |
Core | 4 | 16 |
Electives | 2 | 8 |
Internship | At least one internship of up to six weeks duration must be satisfactorily completed as a graduation requirement | 2 |
Introduction to Research Methods | 1 | 2 |
Research Thesis | 1 | 8 |
The Master of Science in Machine Learning is primarily a research-based degree. The purpose of coursework is to equip students with the right skill set, so they can successfully accomplish their research project (thesis). Students are required to take AI701, MTH701, ML701, and ML703 as mandatory courses.
Students will select a minimum of two elective courses, with a total of eight (or more) credit hours. One must be selected from list based on interest, proposed research thesis, and career aspirations, in consultation with their supervisory panel. The elective courses available for the Master of Science in Machine Learning are listed in the tables below:
Master’s thesis research exposes students to an unsolved research problem, where they are required to propose new solutions and contribute towards the body of knowledge. Students pursue an independent research study, under the guidance of a supervisory panel, for a period of one year.
The MBZUAl internship with industry is intended to provide the student with hands-on experience, blending practical experiences with academic learning.
Code | Course Title | Credit Hours |
INT799 | M.Sc. Internship (up to six weeks) | 2 |
Bachelor’s degree in a STEM field such as computer science, electrical engineering, computer engineering, mathematics, physics and other relevant science and engineering majors, from a university accredited or recognized by the UAE Ministry of Education (MoE). Students should have a minimum CGPA of 3.2 (on a 4.0 scale) or equivalent.
Applicants must provide their completed degree certificates and official transcripts when submitting their application. Senior-level students can apply initially with a copy of their official transcript and expected graduation letter and upon admission must submit the official completed degree certificate and transcript. A degree attestation (for degrees from the UAE) or an equivalency certificate (for degrees acquired outside the UAE) should also be furnished within their first semester at the university.
All submitted documents must either be in English, originally, or include legal English translations. Additionally, official academic documents should be stamped and signed by the university authorities.
Each applicant must show proof of English language ability by providing valid certificate copies of either of the following:
TOEFL iBT and IELTS academic certificates are valid for two (2) years from the date of the exam while EmSAT results are valid for eighteen (18) months. Only standard versions (i.e. conducted at physical test centers) of the accepted English language proficiency exams will be considered.
Waiver requests from eligible applicants who are citizens (by passport or nationality) of UK, USA, Australia, and New Zealand who completed their studies from K-12 until bachelor’s degree and master’s degree (if applicable) from those same countries will be processed. They need to submit notarized copies of their documents during the application stage and attested documents upon admission. Waiver decisions will be given within seven (7) days after receiving all requirements.
A general test certificate is optional and submitting one will be considered a plus during the evaluation.
In a 500- to 1000-word essay, explain why you would like to pursue a graduate degree at MBZUAI and include the following information:
Applicants will be required to nominate referees who can recommend their application. M.Sc. applicants should have a minimum of two (2) referees wherein one was a previous course instructor or faculty/research advisor and the other a current or previous work supervisor.
To avoid issues and delays in the provision of the recommendation, applicants have to inform their referees of their nomination beforehand and provide the latter’s accurate information in the online application portal. Automated notifications will be sent out to the referees upon application submission.
Selected applicants will be invited to participate in an entry exam that will include questions related to the following topics:
Math: Calculus, probability theory, linear algebra, trigonometry and optimization
Programming: Knowledge surrounding specific programming concepts and principles such as algorithms, data structures, logic, OOP, and recursion as well as language–specific knowledge of Python
To enhance the preparedness for the entry exam, applicants are strongly advised to successfully complete the following online courses on Coursera and upload the corresponding completion certificates to their MBZUAI online application:
The exam instructions are available here
Selected applicants will be invited to participate in an online information session with the Admission team.
A typical study plan is as follows:
AI701 Foundations of Artificial Intelligence
MTH701 Mathematical Foundations of Artificial Intelligence
ML701 Machine Learning
ML703 Probabilistic and Statistical Inference
+ 2 elective from list
INT799 Internship (up to six weeks)
ML699 Master’s Research Thesis
RES799 Research Training
ML699 Master’s Research Thesis
AI is permeating every industry. At recent employer engagement events at MBZUAI, there has been representation from multiples sectors including (but not limited to):
Recent job opportunities advertised via the MBZUAI Student Careers Portal include (but not limited to):
Other career opportunities could include (but not limited to):
President and University Professor
Acting Chair of Machine Learning, Professor of Machine Learning, and Director of Center for Integrative Artificial Intelligence (CIAI)
Deputy Department Chair of Machine Learning, and Associate Professor of Machine Learning
Professor of Machine Learning
Professor of Machine Learning
Assistant Professor of Machine Learning
Assistant Professor of Machine Learning
Assistant Professor of Machine Learning
Assistant Professor of Machine Learning
Assistant Professor of Machine Learning
Assistant Professor of Machine Learning
Adjunct Professor of Machine Learning
Adjunct Assistant Professor of Machine Learning
Disclaimer: Subject to change.
We’ll keep you up to date with the latest news and when applications open.