Computer Vision & Artificial Intelligence

Key programme benefits to future students

Students will learn about modern Deep Learning approaches to many machine and computer vision problems across a wide range of industry-focused applications, including object detection, 3D image processing and facial recognition.



This programme is co-designed with industry. It focuses on peer-to-peer and team learning, critical reflection and feedback incorporating coding challenges in AI and Computer Vision to give the student the skills to work confidently in this in-demand area.



Students will have an option to complete a capstone masters project in Computer Vision and AI or to join our Digital Futures and Innovation Stream. The latter is designed for students that are destined to become industry leaders or entrepreneurs.

Autumn Modules

• Introduction to Data Engineering and Machine Learning

• Artificial Intelligence

• Machine Vision

• Computer Vision Systems

• Evolutionary Computation and Humanoid Robotics



Spring Modules

• Introduction to Engineering Research Methods

• Deep Learning at the Edge

• Geometric Computer Vision

• Deep Learning for Computer Vision

• Data Governance and Ethics



Summer Modules

• Digital Futures and Innovation Stream - Strategic Foresight and Systems Change - Designing Market Futures - Futures Mindset and Competence Portfolio

• Master of Engineering Project – Computer Vision and AI

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.



Artificial Intelligence and Computer Vision are engineering subjects that require significant mathematical ability. In particular, Linear Algebra is a key mathematical tool that you will require to be successful in this programme. We strongly suggest that you examine the Linear Algebra Self-Assessment Worksheet. If you can comfortably answer the questions, then you will be well equipped for the programme

1 year full-time, on-campus.

Autumn

Graduate careers

Software Developer with AI specialisation, Data Scientist, Product Managers, Computer Vision Researcher, Machine Learning Engineer