Mohamed bin Zayed University of Artificial Intelligence

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 and international students in the field of Artificial Intelligence.
MBZUAI aims to support the advancement of scientific research, development, transfer, and use of Artificial Intelligence through the introduction of MSc and Ph.D. programs that allow students to fulfill their intellectual
MBZUAI seeks to empower a new generation of AI leaders through exceptional education and a unique model of academia. The University offers graduate level students a range of postgraduate degrees, focusing on core components of the AI industry: Computer Vision, Machine Learning, and Natural Language Processing.

The Academic Programs

Home Study @ MSc Machine Learning

1. Master’s of Science in Machine Learning starting 2021

Program details

Introduction
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.
Apply for the program
Program Competence
Upon completion of the program requirements, the graduate will be able to:

1. Exhibit highly specialized understanding of the modern machine learning pipeline: data, models, algorithmic principles, and empirics.
2. Achieve advanced skills in data-preprocessing and using various exploration and visualization tools.
3. Demonstrate critical awareness of the capabilities and limitations of the different forms of learning algorithms.
4. Obtain advanced capabilities to critically analyze, evaluate, and continuously improve the performance of learning algorithms.
5. Acquire advanced abilities to analyze computational and statistical properties of advanced learning algorithms and their performance.
6. Gain expertise in using and deploying machine learning-relevant programming tools for a variety of complex machine learning problems.
7. Develop advanced problem-solving skills through independently applying machine learning methods to multiple complex problems, and demonstrate expertise in dealing with ambiguity in a problem statement.
8. Apply sophisticated skills in initiating, managing, and completing multiple project reports and critiques on variety of machine learning methods, that demonstrate expert understanding, self-evaluation, and advanced skills in communicating highly complex ideas

2. Doctor of Philosophy in Machine Learning

Program details

Introduction

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.
Apply for this program

Program Competence

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

1. Obtain rigorous mathematical background and advanced reasoning capabilities to express 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 demonstrates 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 demonstrates expert understanding, self-evaluation, and advanced skills in communicating highly complex ideas.

3. Master of Science in Computer Vision

Program details

Introduction

This scientific field studies how computers can be used to automatically understand and interpret visual imagery. It aims to mimic the astounding capabilities of human visual cortex using machine vision algorithms. It studies how an image is created, the geometry of the 3D world and high-level tasks such as object recognition, object detection, and tracking, image segmentation and action recognition. Computer vision has important applications in augmented/virtual reality, autonomous cars, service robots, biometrics and forensics, remote sensing and security and surveillance.
Apply for this program

Program Competence

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

1. Exhibit comprehensive and highly specialized knowledge of computer vision in line with the underlying mathematical and computational principles.
2. Perform critical literature survey and develop new ideas by integrating multidisciplinary knowledge.
3. Apply advanced problem-solving skills to analyze, design and execute solutions for the existing and new problems in computer vision faced by both industry and academia.
4. Become highly skilled in initiating, managing, and completing multifaceted computer vision projects, and be able to clearly communicate concepts, complex ideas and conclusions both orally and in the form of technical reports.
5. Function independently and in a team to address computer vision problems under complex and unpredictable real-world settings.
6. Demonstrate a fundamental understanding of computer vision discipline at an advanced level suitable to pursue a PhD degree and contribute to cutting-edge computer vision research to produce new knowledge or take responsibility to lead innovative and impactful computer vision projects in industry.
7. Manifest the right learning attitude during coursework and research that clearly shows ownership, personal and technical growth and responsibility.
8. Understand legal, ethical, environmental and socio-cultural ramifications of computer vision technologies, and be able to make informed and fair decisions on complex practical issues.

4. Doctor of Philosophy in Computer Vision

Program details

Introduction

This scientific field studies how computers can be used to automatically understand and interpret visual imagery. It aims to mimic the astounding capabilities of human visual cortex using machine vision algorithms. It studies how an image is created, the geometry of the 3D world and high-level tasks such as object recognition, object detection, and tracking, image segmentation and action recognition. Computer vision has important applications in augmented/virtual reality, autonomous cars, service robots, biometrics and forensics, remote sensing and security and surveillance.
Apply for this program

Program Competence

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

1. Master the fundamental knowledge of computer vision and develop expertise in several specialized areas of research in computer vision.
2. Grow expertise in comprehending existing literature, apply reasoning, and master necessary skills and techniques to develop novel ideas that are recognized by the experts of the computer vision discipline.
3. Apply advanced problem-solving skills to analyze, design and execute innovative solutions for the existing and/or new problems faced in both industry and academia.
4. Highly skilled in initiating, managing and completing technically challenging computer vision projects and be able to clearly communicate concepts, highly complex ideas and key findings in the form of technical reports, scientific publications and oral presentations at relevant technical venues.
5. Become an expert in selecting and using programming tools, libraries and other relevant resources to solve real-world computer vision problems.
6. Develop an advanced ability to work independently with substantial authority or in team collaboration with professional integrity to complete highly challenging computer vision projects in a timely manner.
7. Develop a deep understanding of the existing body of knowledge and the ability to develop new knowledge in computer vision that makes students suitable for a role in academia or industry.
8. Practice research ethics and commit to professional responsibilities while conducting cutting edge advancements in computer vision discipline.
9. Understand legal, ethical, environmental and socio-cultural ramifications of computer vision technologies, and be able to take a lead in making informed and fair decisions on complex issues.