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



Autumn Modules

• Introduction to Data Engineering and Machine Learning

• Artificial Intelligence

• Machine Vision

• Computer Vision Systems

• Artificial Intelligence and Governance



Spring Modules

• Introduction to Engineering Research Methods

• Theory and Practice of Advanced AI Ecosystems

• Deep Learning at the Edge

• Geometric Computer Vision

• Deep Learning for Computer Vision



Summer Modules

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

• Option 2: Digital Futures and Innovation



Stream - Digital Futures Lab - Master of Engineering Digital Futures Project

Applicants should hold a bachelor’s degree (NFQ Level 8) with at least a second-class honour, grade 2 (2:2) in a relevant discipline like engineering, computing, mathematics, science or technology discipline, or another discipline where significant math and computing elements can be demonstrated.



The university may shortlist and invite you to an interview.



Linear Algebra is a key mathematical requirement for this programme. If you can answer the questions in the Linear Algebra Self-Assessment Worksheet, you will be well equipped for the course.



Admission to the programme is a competitive process, and unfortunately not all applicants that meet the criteria will be offered a place.



Other Entry Considerations:



We encourage you to apply even if you don’t meet the standard entry requirements, as long as you can show that you have the knowledge, skills, and experience needed for the programme.



At UL, we value all kinds of learning and support different ways to qualify through our Recognition of Prior Learning (RPL) policy.

1 year full-time, on-campus.

Autumn

Graduate careers

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