Available: Part- Time
Duration: 1 Year
Award: NFQ Level 9 Major Award (90 ECTS)
Faculty: Science and Engineering
Fees: For Information on Fees, see section below.
Application Deadline: Monday, August 23, 2021
Register your interest here
to be notified when applications are open.
This UL @ Work Professional Diploma in Computer Vision Systems will introduce students to the principles of computer vision, and rapidly advance their knowledge to state of the art vision systems. Students will learn about modern Deep Learning approaches to many Machine and Computer Vision problems across a wide range of applications, including object detection, 3D image processing and facial recognition.
The programme is specifically designed as a full online (or blended) programme, including video lectures and practical coding challenges to allow students to develop and apply their learning. The programme will be of interest to recent ICT, scientific or Engineering graduates who wish to further specialise in the field of computer vision. The programme will also be of interest to technical professionals seeking to apply computer vision techniques to products and processes within their employment.
The programme will be delivered fully online in 2021/2. Students will study specialist modules in :-
- Introduction to Machine Vision Principles.
- Design and Operation of Machine Vision Systems.
- Geometric Computer Vision.
- Intelligent Visual Computing and Applications.
- Futures Portfolio Project Planning.
Students will experience a supportive and dynamic learning environment in which there will be an emphasis on peer learning, team learning, critical reflection and feedback. Through the virtual learning environment students will have an opportunity to engage with a range of learning methods and problems. Between session students will be supported by faculty and staff online.
On successful completion of this programme, the graduate will be able to:
Utilise classical and state of the art Computer Vision techniques and algorithms to develop new manufacturing process and product solutions.
Breakdown a Computer Vision problem and determine appropriate project management strategies to develop a solution.
Reflect on individual roles within an interdisciplinary process and workplace.
|Applicants are normally expected to hold a primary honours degree in a cognate (related) discipline, (minimum H2.2), or equivalent and have at least 5 years of relevant industrial experience.|
|The course admission team may interview applicants at their discretion as part of the admission process.|
|Alternative Entry Route:|
|Candidates who do not meet the minimum entry criteria may be considered in accordance with the University's policy on the Recognition of Prior Learning. These candidates will be required to submit a portfolio to demonstrate their technical and/or management experience.|
|Alternative Entry Route applicants will be required to undertake an interview and satisfy the course admission team that they have the experience, motivation and ability to complete and benefit from this course.|
What to Include with your Application
Delays in receiving these documents will affect the progress of your application.
- Photo or Scanned original copy of your transcripts for all years of study. (Graduates of UL need only provide us with their Student ID number.)
- Photo or Scanned copy of passport to verify ID and full legal name.
- A copy of your most recent CV.
- Applicants who do not have English as their first language may satisfy English Language requirements:
• If your qualifications have been obtained in a country where English is an official language this will suffice
If this is not available, the following additional documents must be provided:
• English translation of your qualification(s)/transcripts
• English language competency certificate
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