Computer Vision and Artificial Intelligence - MEng Programme content

Gain in-demand computer vision skills for jobs in Ireland and globally with the Master of Engineering in Computer Vision and Artificial Intelligence

EU fees per year €8,500

Non-EU fees per year €21,500

NFQ Level NFQ Level 9 Major

Duration One year

Attendance Full-time

Programme type Taught

Start date September

Award Masters

Key information

Complete full-time over one year
Delivered on campus
Modules taught during autumn and spring semesters
Option to exit after the Spring Semester with a Postgraduate Diploma
Submit dissertation or Engineering Project at the end of summer semester
Option to replace summer semester to develop a digital portfolio with a Digital Futures Innovation steam

Introduction to Data Engineering and Machine Learning (CE4051) covers mathematical and coding skills essential to developing machine learning applications in Python and introduces more advanced machine learning topics.
Artificial Intelligence (CE4041) provides a solid theoretical and practical understanding, knowledge and skill in the application of artificial intelligence and expert systems.
Machine Vision (CE6021) provides a detailed insight into image formation, formats and processing necessary so computers can use machine vision technologies.
Computer Vision Systems (CS6461) equips students with skills for the development of real-world robust computer vision systems.
Artificial Intelligence and Governance (IN6031) provides a comprehensive understanding of the governance, ethics, and social and business impacts of AI.

Books and journal articles needed for the course will be available online through the UL Glucksman Library.

For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules

Introduction to Engineering Research Methods (CE6026) supports students in finding a suitable research topic, developing a detailed specification, and preparing for the academic writing of their report.
Theory and Practice of Advanced AI Ecosystems (CS5024) prepares students to use new technologies for the sharing, composition, reuse, and retrieval of algorithms and data relevant to the production and use of Artificial Intelligence.
Deep Learning at the Edge (EE6008) develops insight into deep learning and associated frameworks relevant to edge computing.
Geometric Computer Vision (CE5002) provides students with the means to use cameras to reconstruct the structure and shape of the environment in which the camera is located.
Deep Learning for Computer Vision (CE5021) equips students with a full understanding of how to design and build deep neural networks for their own applications.

Books and journal articles needed for the course will be available online through the UL Glucksman Library.

For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules

Master of Engineering Project – Computer Vision and AI (CE6025) facilitates students to undertake and complete a significant project, involving an advanced design and implementation task related to Computer Vision and Artificial Intelligence.

A number of students may choose to follow this stream, developing a professional portfolio as an alternative to the traditional project thesis.

Digital Futures Lab (MI6103) enables students to address complex organisational and societal problems through mapping, analysis and creative thinking.
Master of Engineering Digital Futures Project (CE6013) facilitates students to complete a technical prototype based on their portfolio work in the Digital Futures Lab.

Books and journal articles needed for the course will be available online through the UL Glucksman Library.

For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules