Course Details

Course Code(s):
Course Start Date:
1 Year
Postgraduate Diploma
NFQ Level 9 Major Award
Faculty: Science and Engineering
Course Type: Taught
Fees: For Information on Fees, see section below.


Name: Dr Ciaran Eising

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Register your interest here for more information or to be notified when applications are open.

Brief Description

Next Intake: September 2024 

We are delighted to inform you that funding up to 100% is now available through the Springboard/HCI Pillar 1 initiative. For information on eligibility, go to the Fees section on this page.

Funded places are offered on a first-come first-served basis, but these are limited and are strictly subject to Springboard+/HCI eligibility. Once the funded places have been filled, the course may remain open for those who wish to apply for a self-financed place.

This full-time Postgraduate Diploma of Engineering programme in Computer Vision and Artificial Intelligence introduces students to computer vision and rapidly advances their knowledge in state-of-the-art vision systems, artificial intelligence algorithms, and machine learning applications. Students will learn about modern Deep Learning approaches to many machine and computer vision problems across a wide range of applications, including object detection, 3D image processing, and facial recognition.

The programme is developed with industry and focuses on peer and team learning, critical reflection, and feedback incorporating coding activities in AI and Computer Vision so that students are equipped with the skills to work effectively in the area.

Please register your interest to be notified when applications are being accepted to the programme.

Alternative programmes in this discipline include: 

Computer Vision and Artificial Intelligence – MEng (full-time, taught)

Artificial Intelligence for Computer Vision – Professional Diploma (part-time, online)

Artificial Intelligence for Computer Vision – Professional Diploma (part-time, online)

Computer Vision is an extremely popular  Artificial Intelligence and Computer Engineering subfield that allows a computing system to interpret images and infer high-level reasoning.  It is widely used in many diverse industries: manufacturing, social media, automotive, virtual reality, augmented reality, robotics, medicine, security, aerospace, consumer electronics, and increasingly in fields such as agriculture, retail, automated driving, and fitness/sport.

A cursory search on any job listing site will demonstrate that there are hundreds of jobs that list computer vision and image processing as required skills in Ireland, and many thousands in the UK, Europe, and beyond. This programme, therefore, is suitable for those who want to upskill and pursue a career in computer vision and/or artificial intelligence, working in engineering and technical roles, or graduates with a degree in numerate disciplines including Engineering, Computer science and Physics.

In the first semester, you will study technical concepts in artificial intelligence, machine learning, and computer vision. In the second semester, you will take a deeper dive into applications of computer vision and AI, while also delving into transferrable skills in governance, ethics, and research methods. 

Autumn Semester

Spring Semester


  • Introduction to Data Engineering and Machine Learning (CE4051)
  • Artificial Intelligence (CE4041)
  • Computer Vision Systems (CE6023)
  • Evolutionary Computation and Humanoid Robotics (CS6271)
  • Introduction to Engineering Research Methods (CE6026)
  • Data Governance and Ethics (IN6062)
  • Deep Learning at the Edge (EE6008)
  • Geometric Computer Vision (CE5002)
  • Deep Learning for Computer Vision  (CE5021)





Applicants for a Postgraduate Diploma programme must normally have a first or second-class Level 8 honours degree (NFQ or other internationally recognised equivalent) in a relevant or appropriate subject, or equivalent prior learning that is recognised by the University as meeting this requirement. Applicants must also satisfy the English Language Requirements* of the University. The University reserves the right to shortlist and interview applicants as deemed necessary.

The relevant or appropriate subjects include:

Your undergraduate degree must be in a numerate and relevant discipline, e.g., relevant engineering, computing, mathematics, science or technology discipline, or another discipline where significant math and computing elements can be demonstrated.

*  English Language Requirements: Please refer to


  • Qualification transcripts and/or certificates (including certified English translations if applicable)
  • A one page supporting statement
  • A copy of your birth certificate or passport
  • If your qualifications have been obtained in a country where English is an official language this will suffice
  • If this is not available, the following additional documents must be provided:
    • English translation of your qualification(s)/transcripts
    • English language competency certificate

For more information Click Here

EU - €7,000 

Non-EU - €18,087

Springboard/HCI Funding - Candidates who satisfy the eligibility criteria under Springboard+ can qualify for 90% or 100% funding subject to the availability of places. To clarify eligibility please go to

Further information on fees and payment of fees is available from the Student Fees Office website. All fee related queries should be directed to the Student Fees Office (Phone: +353 61 213 007 or email

Please click here for information on funding and scholarships.