Course Details

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


Name: Dr Ciaran Eising
Name: Dr Tony Scanlan

Express Interest

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

Brief Description

This full-time Master of Engineering programme in Computer Vision and Artificial Intelligence introduces students to the principles of 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 in collaboration with industry and focuses on peer and team learning, critical reflection and feedback incorporating coding challenges in AI and Computer Vision so that students are equipped with the skills to work confidently in the area.

Computer Vision is an extremely popular subfield of Artificial Intelligence and Computer Engineering that allows a computing system to interpret images and infer high-level understanding and 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. In the Summer Semester, students will either complete a capstone project in the areas on Computer Vision and/or Artificial Intelligence, or they will generate a portfolio through the Digital Futures and Innovation stream.

Autumn Semester

Spring Semester

Summer Semester

  • CE4051 - Introduction to Data Engineering and Machine Learning
  • CE4041 - Artificial Intelligence
  • CE6021 - Machine Vision
  • CE6023 - Computer Vision Systems
  • CS6271 - Evolutionary Computation and Humanoid Robotics
  • EE4052 - Introduction to Engineering Research Methods
  • IN6062 - Data Governance and Ethics
  • EE6008 - Deep Learning at the Edge
  • CE5002 - Geometric Computer Vision
  • CE5021 - Deep Learning for Computer Vision


Option 1: Master of Engineering Project – Computer Vision and AI

Master of Engineering Project – Computer Vision and AI - CE6025


Option 2: Digital Futures and Innovation Stream

A small cohort may elect to join the Digital Futures and Innovation programme, in which you will develop a portfolio in place of the project thesis.

Strategic Foresight and Systems Change - MG5013

Designing Market Futures - MG5023

Futures Mindset and Competence Portfolio - MG5003

Applicants for a Master’s 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 - €6,950 

Non- EU - €17,702

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.