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Artificial Intelligence - MSc (Online)

Progress your career as an IT professional by gaining advanced skills in AI with UL’s two-year, part-time Master of Science in Artificial Intelligence.

Key information

EU fees per year €5,940
Non-EU fees per year €8,820
NFQ Level NFQ Level 9 Major
Duration Two years
Attendance Part-time
Programme type Taught, Professional / Flexible
Delivery Online
Start date September
Award Masters (MSc)

Programme Intake: September – There is an option to enter this Masters in January if you have already completed the Certificate in AI  or if you satisfy suitability criteria. Contact programme administrator Claire Gallery (claire.gallery@ul.ie) for further information. 

This programme qualifies for subsidised fees from Technology Ireland ICT Skillnet. See fees section for more details. 


Progress your career as an IT professional with in-demand skills in AI and Machine Learning with UL’s two-year, part-time Master of Science (MSc) in Artificial Intelligence.  

The programme provides IT professionals and those migrating from associated disciplines with a deep understanding of the modern AI and machine learning approaches, with a focus on practical applications, as well as the risks and ethical issues associated with AI.   

In the second year, students are given the option to focus on machine learning, natural language processing or computer vision and present a dissertation on a relevant AI-related problem.  

The programme was developed with extensive input from Technology Ireland ICT Skillnet and UL’s Industry Advisory Board to ensure the content is relevant to industry. You may be able to avail of subsidised fees from Technology Ireland ICT Skillnet. See fees section for more details. 

During this programme, you will

  • Acquire knowledge and skills in the application of Artificial Intelligence and Machine Learning. 

  • Explore relevant subjects in a self-driven manner, with expert support from module leaders and moderators. 

  • Gain an understanding of the key principles and methods in Machine Learning, Natural Language Processing or Computer Vision. 

  • Benefit from a mixed learning process with an emphasis on practical applications. 

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