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During this programme, you will:  

• Focus on deep learning applications and critical computer vision applications, including facial recognition and 3D reconstruction. 

• Explore Machine Vision and Image Processing principles and key topics such as linear image processing, feature detection and essential object detection. 

• Use advanced tools and techniques used in industry for real-world computer vision applications. 

• Develop critical thinking and problem-solving skills for designing and evaluating AI-powered visual systems across diverse sectors. 

Key information: 

• Complete part-time over one year 

• Delivered online   

• Modules taught during autumn and spring semesters 

• Approx. 12 weeks per semester 

• Submit Future Focused Professional Portfolio at the end of the final semester  

• Can be used to complete 30 credits towards Master of Professional Practice (MPP) or MSc Engineering Practice 

• Modules with (M) beside them can be taken as independent micro-credential  

You will learn through a blend of:  

• Lectures, workshops, and hands-on activities  

• Reflective practice and guided research  

• Regular feedback from faculty and peers  

Part-time considerations:  

• Designed for working professionals  

• Evening or recorded lectures  

• Additional prep and group work time  

• Timetable provided after registration 

Year 1 

Autumn Semester 

• examines the application of deep learning to the key computer vision tasks of image classification, object detection and semantic segmentation.  

• Machine Vision & Image Processing (M) (CE5011) focuses on Machine Vision and Image Processing principles, introducing key topics such as linear image processing, feature detection and essential object detection. 

• discuss the future of technology, the future of markets, the future of society and work collaboratively to identify key trends impacting your role and organisation. 

Spring Semester 

• explores the significance of the structure and shape of the environment in which a camera is located. 

• (CE5012) focuses on deep learning applications to critical computer vision applications, including facial recognition and 3D reconstruction. 

• provides an opportunity to demonstrate independent and self-determined learning through the creation of your own individual portfolio. 

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  

• Applicants should hold a bachelor’s degree ( Level 8) with at least a second-class honour, grade 2 (2:2) in a relevant or appropriate subject. 

• The university will 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. 

International students:   

For details on country-specific qualifications visit postgraduate entry requirements for international students. 

Checklist of documents to provide:    

• *Academic transcripts and certificates
• UL graduates only need to provide their student ID.
• Copy of your birth certificate or passport
• English translation of your qualifications and transcripts
• Copy of your CV 

English Language: 

• English Language Competency certificate
• For details on accepted language qualifications visit English Language Requirements 

Guidelines on Completing your Application   

• To make sure we can review your application quickly, please:
• Upload all documents. Your application can’t be reviewed until we have all the documents on the checklist. 
• Title the documents you are uploading. For example, "Personal Statement", "Undergraduate Transcript", "Postgraduate Transcript", "English Language Certificate" etc. 
• *If you are waiting to graduate, submit your application with the documents you have to date, you don’t need to have finished final exams before applying. 

EU - €5,250

Please note that international study visas are only available to students studying full-time in Ireland. This programme does not qualify for a study visa. 

Annual fees are billed by semester. Once registered, students may be eligible to apply for a monthly payment plan.  

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 student.fees.office@ul.ie).  

 
Funding 

Find further information on funding and scholarships. 

This course can lead to the following sectors and careers:  

• Data Scientists
• Software Developers
• Engineers
• Researchers 

Still Curious?  

The team regularly host and take part in webinars to support future students. If you would like to learn more or ask questions at an online information session, click below.     

Online Information Sessions