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Next Intake: September 2024
Artificial intelligence (AI) with computer vision skills has seen a business application surge in recent years. Computer vision refers to the ability of computers to interpret and understand the visual world, including images and videos. AI with computer vision skills combines this ability with machine learning algorithms to create intelligent systems that can analyse, process, and interpret vast amounts of visual data in real time. Taking an example of use from the manufacturing industry, computer vision algorithms can analyse images of products on an assembly line to identify defects and other issues that would be difficult for humans to detect. This can help improve product quality and reduce waste, leading to cost savings for manufacturers.
We offer a part-time, online Professional Diploma in AI for Computer Vision that will introduce you to the principles of computer vision, develop your knowledge of cutting-edge vision systems, and empower you to apply these skills to your workplace. You will learn about modern Deep Learning approaches to many machine and computer vision problems across a wide range of industry-focused applications, including object detection, 3D image processing and facial recognition.
This innovative Level 9 programme is co-designed with industry. It focuses on peer-to-peer and team learning, critical reflection and feedback incorporating coding challenges in AI and Computer Vision to give you the skills to work confidently in this in-demand area.
Note* This programme is available at both an introductory and advanced level. Information on each pathway can be found under the Programme Content tab below.
UL@Work programmes are co-designed with industry to ensure skills transfers are industry-responsive for current and future needs. Our programmes are developed for working professionals and are designed to be flexible and accessible. You can take it online and from anywhere worldwide.
Stack your learning with Microcreds:
Not quite ready to commit to a full professional diploma? Consider trying a microcredential. You can stack your microcred credits towards a professional diploma at a later date. Modules listed within the Programme Content with an (M) beside them are MicroCreds and can be taken independently.
Build Your Master Plan: Stack Your Way to Success: If you are using this Professional Diploma as the final 30 ECTS Credits to stack into our Master of Professional Practice (MPP) you will need to apply via the MPP page HERE.
Applicants eligible for ICT Skillnet funding must apply in the Summer for the Sept start. The deadline to apply for funding is 17th August 2023.
This programme is suitable for those who wish to upskill in computer vision for improved accuracy and efficiency within their workplace. Also, it offers widened opportunities for career advancement. It is of great benefit to a wide range of working professionals, including:
Software Developers: AI for Computer Vision is an emerging field that requires software developers to be familiar with algorithms and computer vision techniques. This programme will help you to enhance your skills and stay up-to-date with the latest developments in this field.
Data Scientists: Data scientists collect, analyse, and interpret large amounts of data. This programme will enable you to extract valuable insights from visual data.
Engineers: Engineers, especially those in robotics, autonomous vehicles, drones, manufacturing, public safety and social media, will benefit from understanding computer vision techniques. This new knowledge and skills will help you develop more sophisticated and advanced systems.
Product Managers: Product managers are responsible for managing the development of products and services. Understanding AI for computer vision will empower you to develop new products and services that leverage visual data.
Researchers: Computer science, artificial intelligence, and robotics researchers will benefit from understanding the latest developments in AI for computer vision. This will help you develop new algorithms and techniques to advance the field further.
Overall, this AI for Computer Vision programme benefits those in technical roles which deal with visual data. Graduates with a degree in numerate disciplines, including Engineering, Computer science and Physics, would also benefit from this programme.
We are delighted to offer this Level 9 Professional Diploma at both introductory and advanced levels so that you can engage with the programme at a suitable level. The introductory programme, Scientific Computing & Computer Vision pathway, will arm you with introductory knowledge if you are new to computer vision and artificial intelligence (AI) and without experience in Python. The advanced programme, Artificial Intelligence & Computer Vision pathway, challenges those with prior experience in Python to deepen their knowledge and skills. This approach allows you to access the programme at a level that works for you to make the most of your learning experience. We would recommend the advanced pathway to those who have previously completed a MSc in AI programme or have good knowledge of machine learning and python principles.
See the module content for the introductory and advanced options below. When you register for this programme, you will be prompted to choose the pathway you wish to enrol in.
Download the programme brochure HERE
Introduction to Scientific Computing for AI (M)
Geometric Computer Vision
Deep Learning for Computer Vision
Geometric Computer Vision
FREQUENTLY ASKED QUESTIONS
Who is this Professional Diploma in AI for Computer Vision for?
A programme in AI for computer vision would be beneficial for anyone interested in developing applications or systems that require image or video analysis. This is a rapidly growing field with a high demand for skilled professionals.
Why should you/your employee sign up?
Computer vision has applications in various industries, such as healthcare, retail, manufacturing, and autonomous vehicles. By taking this programme, you/your employee can learn how to apply computer vision techniques to solve real-world problems in your organisation, such as:
- Automation - With computer vision skills, you can automate many repetitive and time-consuming tasks, such as quality control, inspection, and data analysis. This can save a significant amount of time and money while improving accuracy and efficiency.
- Improved customer experience - Computer vision will help your business to better understand and respond to your customers' needs. For example, computer vision can be used to analyse customer behaviour in your retail store, providing insights that can be used to optimise your store's layout or improve product placement.
- Competitive advantage - Companies that can leverage computer vision technology can gain a competitive advantage over those that don't. These skills will empower you to make better business decisions and improve the bottom line by automating tasks and gaining deep and meaningful insights.
- Innovation - Computer vision technology is constantly evolving, and businesses that invest in this area are well-positioned to stay ahead of the curve. By staying up to date with the latest developments in computer vision, your business can identify new opportunities for growth and innovation.
Can you give some more industry examples of AI for Computer Vision in use?
- In retail, computer vision can track inventory and analyse customer behaviour. For example, AI algorithms can analyse video footage to track customer movement patterns within a store, identify products that are frequently picked up but not purchased, and even predict when inventory is running low and needs to be restocked.
- In healthcare, AI with computer vision skills analyses medical images such as X-rays and CT scans to help doctors diagnose and treat patients more quickly and accurately. For example, computer vision algorithms can analyse X-rays to detect early signs of lung cancer or analyse MRI scans to identify areas of the brain that are affected by neurological conditions.
- Another area where AI with computer vision skills is making a difference is autonomous vehicles. Self-driving cars rely on computer vision algorithms to analyse the road ahead, detect obstacles, and decide how to navigate safely. This technology has the potential to revolutionise transportation and make our roads safer.
As AI with computer vision skills advances, we expect more industries to adopt this technology to improve efficiency, reduce costs, and enhance overall performance.
Can you give an example of an assignment?
Perform Classification of a Histopathology Dataset using transfer learning. - Applying transfer learning to biomedical data is difficult as the target domain is very different to the source ImageNet domain used to train the Neural Networks often used as a feature extractor for biomedical data. In this assignment, you will create a base neural network model with appropriate classifier layers for the biomedical data and fine-tune the model to maximise performance on the biomedical dataset.
How many hours per week? And what is the split between lecture and tutorial time?
This part-time programme is delivered online with a 15 to 18hr commitment per week. A one-hour weekly live session will be held at 6pm on a nominated weeknight, and tutorials will be held at a time that suits students. All material will be recorded for self-directed learning; however, you will be supported by your lecturers and tutors.
What companies currently use AI for Computer Vision?
Many companies use AI for computer vision as it is a rapidly growing field with numerous applications across various industries. Some examples where AI for Computer Vision is prevalent include but are not limited to Adobe, AMCS, Amazon, Analog Devices, Apple, Cainthuis, Collins Aerospace, Dataminr, Emdalo Technologies, Ericsson, Facebook, Google, Huawei, IBM, Intel, Jaguar Land Rover, Johnson & Johnson, Microsoft, NVIDIA, Qualcomm, Shutterstock, Tesla, Twitter, Valeo Vision Systems, Xperi, GM.
What software/ programmes will I be using?
Python packages such as Numpy, sklearn, OpenCV, and Tensorflow with access to this software via Google Colab. However, it is worth noting that you do not need to have experience with these tools already; you will learn these in this programme.
Do I need access to anything? For example, data, software?
Access to a PC and a good internet connection suitable for live video lectures.
How are learners assessed on this programme?
There are no terminal exams on this programme. Assessment will be continuous; you will be asked to prepare a media plan that will be developed for your chosen company.
When does this programme start?
This programme starts in September 2023 and finishes in May 2024. It is part-time and delivered online.
Who is leading this programme?
Dr Tony Scanlan
Dr Scanlan is a Senior Research Fellow in the UL Dept. of Electronic & Computer Engineering. He has extensive experience in microelectronics and signal processing in association with multinational and SME industrial partners. Dr Scanlan's current research interests are applying Artificial Intelligence (AI) & computer vision to manufacturing inspection, environmental monitoring and consumer & media applications.
Dr Ciarán Eising
Dr Eising has extensive experience working in computer vision, having worked for >15 years designing computer vision algorithms and systems for driver assistance and automated driving solutions with Valeo Vision Systems. His research in UL focuses on artificial intelligence and computer vision applications in areas such as medical imaging, waste management and automated driving.
Dr Pepijn van de Ven
Dr. van de Ven is a Senior Lecturer in Artificial Intelligence and Machine Learning and a Course Director for UL's national online MSc in AI, an industry-driven, fast-paced masters to upskill Ireland's workforce in using Artificial Intelligence.
Applicants are normally expected to hold a primary honours degree in a related discipline, (minimum H2.2).
Alternative Entry Route:
In accordance with the University's policy on the Recognition of Prior Learning candidates who do not meet the minimum entry criteria may be considered. These candidates will be required to submit a portfolio to demonstrate their technical and/or management experience. An interview with the course admission team is also required to ensure candidates have the experience, motivation, and ability to complete and benefit from this course.
What to Include with 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.
English Language Requirements:
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
*The deposit is required once an offer is issued to secure a place.
Applicants may be eligible for grant-aided fees from ICT Skillnet. For information, email email@example.com. The deadline to apply for this is 17th August 2023.