Students studying at computers

Human Centered Artificial Intelligence / Intleacht shaorga daonlárnaithe

Course Title: Master of Science in Computing in Human Centred Artificial Intelligence

The minimum entry requirement for standard entrants to the course is a 2:2 (GPA 2.5 or equivalent), in a Bachelor of Science in Computing (Level 8) or a cognate discipline or equivalent. Candidates not attaining this standard level must achieve an acceptable standard for progression by other means approved by QQI. All applicants must have competence in spoken and written English. Candidates may be interviewed to determine eligibility.

If English is not your first language you will need to provide evidence of your English language proficiency as detailed on our website. Applicants for this programme should have a minimum IELTS (Academic Version) English Proficiency of 6.5 overall (or equivalent) with nothing less than 6 in each component.

The digital transformation of organizations and society is in full swing, and Artificial Intelligence (AI) is playing an increasing role in this.

AI systems can used to automatically determine bank loan eligibility, for recognition of dangerous situations through image processing, for assessing medical needs. However, the use of AI also carries challenges, from biased implementations based on faulty data to losing understanding and control over complex systems. How do we ensure that Artificial Intelligence is used for the common good? In the M.Sc. Human Centered AI you learn how to build and apply AI, and how to deal with the societal choices that come with it.

This course has been developed by a consortium of ten organisations across European Universities, Excellence Centres and SMEs. On this course you will develop broad practical knowledge for the creation of Human Centred AI systems. You will also be trained in explainable AI, compliance by design and implementing systems in real world organisations empowering you to make the right decisions about the use of AI with human concerns at the centre.

Further details on this course can be found here.

Semester 1

  • Statistics 
  • Data Analysis and Programming 

Semester 1 & 2

  • Artificial Intelligence and Machine Learning Modelling
  • Ethics & IT
  • Research Methods and Proposal Writing 

Semester 2

  • Future of Artificial Intelligence and Learning
  • Society and AI: Risk and Compliance
  • Human Centric Deep Learning
  • Research Thesis (Human Centred AI)

This course will be delivered in the classroom – Daytime delivery 4 days per week.

Applications for this course are now open



TU Code



Level 9


Masters of Science


1 year

Course Type


Mode of Study

Full Time

Method of Delivery


Commencement Date

September 2023



Virtual Tour




Fees (Non-EU)


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Dr. Barry Feeney

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Dr. Rajesh Jaiswal