MSc in Artificial Intelligence and Machine Learning

Key Points

Write to us for more information

Artificial Intelligence (AI) is one of the most exciting areas of computer science and engineering. AI and machine learning (ML) address the challenge of creating machines that have the ability to learn, adapt, and exhibit intelligence. AI research is revolutionizing our lives and is leading us to a world with autonomous vehicles, automated trading in stock markets, AI-assisted surgery, AI-controlled power grids, smartphones that can recognize objects/faces/speech, search engines that can translate languages, video games that exhibit responsive, adaptive and intelligent behavior.

This unique new program embraces new trends in AI by combining established AI techniques such as:

Unsupervised / supervised / reinforced learning
Deep learning
Parametric / non-parametric regression and classification
Evolutionary Computing
Bayesian networks and search algorithms
With emerging disciplines and technologies such as:

Deep reinforcement learning
Causality modeling
Bioinspired Robotics
Evolutionary Robotics
Humanoid Robotics
Game-inspired behavior modeling
Automatic compliance check
Automatic workflow synthesis
Machine-assisted correction
Probabilistic programming and explainable artificial intelligence.

The emphasis is on applying these techniques to a variety of application areas: text analytics and natural language processing, computer vision, gaming, intelligent manufacturing, predictive maintenance, motion and planning, business analytics, finance, and many others.

Career options

This course prepares students for industry careers in data analytics, data science, machine learning and artificial intelligence. It also aims to provide students with the theoretical knowledge to potentially become high-profile PhD candidates and to be able to conduct high-profile research in AI.

Program structure

YEAR 1

Semester 1 – Fall

Introduction to data engineering and machine learning
Evolutionary computing and humanoid robotics
Text analysis and natural language processing
Artificial intelligence for games
Machine vision

Semester 2 – Spring

Artificial intelligence and machine learning
Deep reinforcement learning
Probabilistic and explainable AI
Theory and Practice of Advanced AI Ecosystems
Research methods and project specification

Semester 3 – Summer

Artificial Intelligence and Machine Learning Project

Admission requirements

Applicants must have a first or upper second class (NFQ or other internationally recognised equivalents) level 8 degree in a relevant or appropriate subject (Computer Science, Computer Engineering programmes or level 8 Science programmes that have sufficient mathematical and programming skills), or equivalent prior learning that is recognised by the University as fulfilling this requirement.
In the case of international candidates, the foreign equivalent is required. In addition, a degree officially translated into English will be required.
IELTS 6.5, with no less than 6 in any component (or its internationally recognised equivalent).