Postgraduate Diploma in Science in Computing

This module introduces the principles and practices of data mining, from preprocessing and feature engineering to advanced tasks like classification, clustering, and anomaly detection. Learners gain hands-on experience with popular tools, explore ethical considerations such as fairness and privacy, and engage with the latest research and real-world applications to develop practical, responsible data mining skills.

This module aims to introduce learners to mobile application development. Learners explore the differences in the computation model between desktop and mobile. Learners are also exposed to the reduced capabilities of this hardware and assess how this impacts their application development. They are also introduced to the sensors available on these devices and how they can be exploited. Learners evaluate advanced topics in mobile applications including different form factors (including, smartwatch, tv, etc.), VR and AR applications, integration with the web and cloud.

This module introduces concurrency and parallel programming, covering threading, memory models, synchronisation, and solutions to challenges like deadlocks. Learners explore distributed systems, including architectures, consensus algorithms, and the CAP theorem, as well as applications such as sorting, matrix operations, and image processing. Emerging topics like cloud computing, distributed machine learning, and edge computing are integrated, equipping students to design scalable, fault-tolerant, and efficient systems.

This module aims to significantly deepen the learners’ research skills, both in relation to their module related assignments and later in the completion of their major dissertation/dissertation by practice. Specifically, it extends their abilities as self-directed learners by equipping them with the appropriate vocabulary for reflecting on, critiquing, and evaluating their own work and that of others. Throughout the module, they are required to engage in a number of research methodologies and current research issues and trends in computing science. The module also addresses the need for good project management skills and techniques for the successful delivery of any project.

This module develops a strong understanding of the principles, technologies, and architectures behind modern data communications networks. Learners design and implement network configurations, assess performance, and explore cutting-edge innovations and emerging trends. The module also covers network security, examining common vulnerabilities and applying protective measures such as firewalls, anti-malware tools, and other defences to safeguard data and maintain network integrity.

The module aims to introduce learners to Agile Software Development practices. Learners are introduced to the Agile Manifesto and methods and, through practical agile software development, create a software artefact. Learners work in groups to realise a software solution to a problem proposed by a customer. They learn to work with the customer at all stages creating user stories, designing sprints, and reviewing sprints.

The module aims to introduce learners to cloud computing infrastructure. Learners evaluate state-of-the-art solutions offered by major cloud providers. Learners also explore important topics of research around the cloud such as energy optimisation, and the efforts to introduce standardisation in the cloud to give them an appreciation for the current and future direction of cloud-based services. Learners are given the opportunity to develop applications for a cloud-based platform and evaluate the differences between normal computation and a cloud-based model.

This module reviews the essentials of artificial neural networks before exploring advanced architectures such as CNNs, RNNs, LSTMs, transformers, and large language models. Learners study autoencoders, GANs, and reinforcement learning techniques like Q-learning, with a strong emphasis on practical implementation using popular tools. Recent developments in deep learning and generative AI are examined through hands-on exercises and analysis of cutting-edge research.

Study Mode: Full-Time

Dublin: EUR 6,550.00

Study Mode: Part-Time

Dublin: EUR 6,550.00

Study Mode: Full-Time

Please refer to the Irish/EU Living Abroad Fees.

Study Mode: Full-Time

Please refer to our Non-EU Tuition Fees section.

Non-EU students: a Student Services and Administration fee of EUR200 is payable each academic year in addition to the fees quoted below.