Artificial Intelligence & Machine Learning

Key programme benefits to future students Opportunities for further education at the PhD level.



Graduates are equipped with skills for applying machine learning techniques to a large variety of application areas: text analytics and natural language processing, machine vision, games, smart manufacturing, predictive maintenance, motion and planning, business analytics, finance and many others.



Key Facts

AI research is revolutionising our lives and leading us to a world with self-driving cars, automated trading on 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 behaviour.

Autumn Modules

• Introduction to Data Engineering and Machine Learning

• Evolutionary Computation and Humanoid Robotics

• Text Analytics and Natural Language Processing

• Artificial Intelligence for Games

• Machine Vision



Spring Modules

• Artificial Intelligence and Machine Learning

• Deep Reinforcement Learning

• Probabilistic and Explainable AI

• Theory and Practice of Advanced AI Ecosystems

• Research Methods and Project Specification



Summer Modules

• Artificial Intelligence and Machine Learning Project

Applicants should hold a bachelor’s degree (NFQ Level 8,) with at least a second-class honours, grade 2 (2:2) in a relevant or appropriate subject like computer science, computer engineering programmes, or science programmes that have sufficient mathematical and programming skills.

Other Entry Considerations:



We encourage you to apply even if you don’t meet the standard entry requirements, as long as you can show that you have the knowledge, skills, and experience needed for the programme.



At UL, we value all kinds of learning and support different ways to qualify through our Recognition of Prior Learning (RPL) policy.

1 year full-time, on-campus.

Autumn

Graduate careers

This course prepares students for industry careers in data analytics, data science, machine learning and AI. It also aims to give the students the theoretical knowledge to potentially become high profile PhD candidates and who can carry out high profile research in AI.