Doctor of Philosophy in Machine Learning

General

Program Description

Doctor of Philosophy in Machine Learning

Upon completion of the program requirements, the graduate will be able to:

  1. Obtain rigorous mathematical background and advanced reasoning capabilities to express a comprehensive and deep understanding of the pipelines at the frontier of machine learning: data, models, algorithmic principles and empirics.
  2. Master a range of skills and techniques in data-preprocessing, exploration, and visualization of data-statistics as well as complex algorithmic outcomes.
  3. Have a critical awareness of the capabilities and limitations of the different forms of learning algorithms and the ability to critically analyze, evaluate, and improve the performance of the learning algorithms.
  4. Grow expert problem-solving skills through independently applying the principles and methods learned in the program to various complex real-world problems.
  5. Develop a deep understanding of statistical properties and performance guarantees, including convergence rates (in theory and practice) for different learning algorithms.
  6. Become an expert in using and deploying machine learning-relevant programming tools for a variety of machine learning problems.
  7. Grow proficiency in identifying the limitations of existing machine learning algorithms and the ability to conceptualize, design, and implement an innovative solution for a variety of highly complex problems to advance the state-of-the-art in machine learning.
  8. Able to initiate, manage, and complete research manuscripts that demonstrate expert self-evaluation and advanced skills in communicating highly complex ideas related to machine learning.
  9. Obtain highly sophisticated skills in initiating, managing, and completing multiple project reports and critiques on a variety of machine learning methods, that demonstrate expert understanding, self-evaluation, and advanced skills in communicating highly complex ideas.

The minimum degree requirements for the Ph.D. in Machine Learning are 59 Credits, distributed as follows:

  • Core Courses: 4 Courses (15 Credit Hours)
  • Elective Courses: 2 Courses (8 Credit Hours)
  • Research Thesis: 1 Course (36 Credit Hours)

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Core Courses

Ph.D. in Machine Learning is primarily a research-based degree. The purpose of coursework is to equip students with the right skillset, so they can successfully accomplish their research project (thesis). Students are required to take COM701, as a mandatory course. They can select three core courses from a concentration pool of eight in the list provided below:

Code Course Title Credit Hours
COM701 Research Communication and Dissemination 3
ML701 Machine Learning 4
ML702 Advanced Machine Learning 4
ML703 Probabilistic and Statistical Inference 4
ML704 Machine Learning Paradigms 4
ML705 Topics in Advanced Machine Learning 4
ML706 Advanced Probabilistic and Statistical Inference 4
AI701 Artificial Intelligence 4
AI702 Deep Learning 4

Elective Courses

Students will select a minimum of two elective courses, with a total of eight (or more) credit hours (CH) from a list of available elective courses based on interest, proposed research thesis, and career perspectives, in consultation with their supervisory panel. The elective courses available for the Ph.D. in Machine Learning are listed in below table:

Code Course Title Credit Hours
MTH701 Mathematical Foundations for Artificial Intelligence 4
MTH702 Optimization 4
CS701 Advanced Programming 4
CS702 Data Structures and Algorithms 4
DS701 Data Mining 4
DS702 Big Data Processing 4
CV701 Human and Computer Vision 4
CV702 Geometry for Computer Vision 4
CV703 Visual Object Recognition and Detection 4
NLP701 Natural Language Processing 4
NLP702 Advanced Natural Language Processing 4
NLP703 Speech Processing 4
HC701 Medical Imaging: Physics and Analysis 4

Research Thesis

Ph.D. thesis exposes students to cutting-edge and unsolved research problems in the field of Machine Learning, where they are required to propose new solutions and significantly contribute to the body of knowledge. Students pursue an independent research study, under the guidance of a supervisory panel, for a period of 3-4 years.

Code Course Title Credit Hours
ML799 Ph.D. Research Thesis 36
Last updated October 2019

About the School

Overview The Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, is a graduate-level, research-based academic institution that offers specialized degree programs for local a... Read More