Artificial Intelligence for Computer Vision - Professional Diploma Programme content
Create intelligent systems that can analyse, process, and interpret vast amounts of visual data in real time with this one-year, part-time online programme.
Key information
EU fees per year
€5,000
NFQ Level
NFQ Level 9 Minor
Duration
One year
Attendance
Part-time
Programme type
Taught, Professional / Flexible
Delivery
Online
Start date
September
Award
Professional Diploma
Key information
- Complete part-time over one year
- Delivered online
- Modules taught during the autumn and spring semesters
- 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
Programme content
Core modules
- Deep Learning for Computer Vision (CE5021) 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.
- Future Focused Professional Portfolio 1 (MN5141) 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.
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
Core modules
- Geometric Computer Vision (CE5002) explores the significance of the structure and shape of the environment in which a camera is located.
- Intelligent Visual Computing and Applications (CE5012) focuses on deep learning applications to critical computer vision applications, including facial recognition and 3D reconstruction.
- Future Focused Professional Portfolio 2 (MN5152) 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 Book of Modules
