PhD in
Machine Learning
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Overview
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.
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Full time Mode -
60 Credits -
On Campus Location
The Machine Learning (ML) Department at MBZUAI is dedicated to imparting a world-class education in ML to our students. From foundational principles to advanced applications, our research-intensive education model will provide our students theoretical concepts to test under supervision from senior AI researchers in the field as they tackle real-world problems and produce meaningful results.
Kun Zhang
Acting Chair of Machine Learning, Professor of Machine Learning, and Director of Center for Integrative Artificial Intelligence (CIAI)
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A typical study plan is as follows:
SEMESTER 1 ML801 - Foundations and Advanced Topics in Machine Learning (4 CR)+ 2 Electives (8 CR)
SEMESTER 2
ML814 - Selected Topics in Machine Learning (4 CR)+ 2 Electives (8 CR)
SUMMER
INT899 INT899 Internship (up to four months)SEMESTER 3
ML899 Ph.D. Research ThesisRES899 Research Training
SEMESTER 4
ML899 Ph.D. Research ThesisSEMESTER 5
ML899 Ph.D. Research ThesisSEMESTER 6
ML899 Ph.D. Research ThesisSEMESTER 7
ML899 Ph.D. Research ThesisSEMESTER 8
ML899 Ph.D. Research ThesisDisclaimer: Subject to change.
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