Edge Computing

Key programme benefits to future students

The course programme targets employment needs by incorporating practical modules and lab/tutorial content focusing on edge computing areas such as Internet of things (IoT), Communications, Artificial Intelligence (AI), Deep Learning, Cloud Computing, Software Programming and Network Design/ Security.



The programme design mixes face-to-face learning approaches with blended learning activities educating students about fundamental edge computing technologies. The course cultivates critical thinking, problem-solving and decision-making skills, which are highly transferable.



Students will complete a capstone masters project to apply the knowledge and skills they have learned in the programme. This equips candidates with valuable hands-on experience, exposes them to real-world applications and opens doors to exciting career opportunities in a rapidly evolving digital landscape.

Autumn Modules

• Introduction to Data Engineering and Machine Learning

• Advanced Programming

• Signal Processing for Communications

• Converged Networks

• Applied Cloud Computing



Spring Modules

• Deep learning at the Edge

• Future Networks

• Real-Time Embedded Systems

• Communications & Security Protocols

• MEng Project 1: Planning and Research Methods



Summer Module

• MEng Project 2: Design and Implementation

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



The university may shortlist and invite you to an interview.



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

Edge computing design and applications engineer, Network designer and solutions architect, Software engineer and consultancy personnel, Machine Learning engineer, Software developer, Internet of Things (IoT) engineer, Design group leaders, Junior project managers, Software systems managers, Researcher, Doctorate postgraduate studies.