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Computer Science ProgrammeSenior Sophister

Senior sophisters can elect to follow the MCS programme with the intention of graduating with a Master in Computer Science (MCS) after successfully completing five years of study, or can finish after 4 years of study with the intention of graduating with a BA (Mod) in Computer Science. All Senior Sophister Students follow the same programme in Michaelmas term, and in Hilary term the MCS students take an Internship while the BA (Mod) students take an individual project and a group project.

Senior sophister students select whether they are intending to take the five year Masters programme by submitting an application for the Masters programme and Internship programme (Note: it is one form, and has to be submitted by the deadline which is typically in early October in their Senior Sophister year; The deadline is on the Internship programme page). Students who do not submit an application automatically take the four year Moderatorship programme.

Prospective students should read the brief descriptions of the courses below the tables which follow. Current students should follow the links (to the eLearning environment, "Blackboard", or to the module websites) or refer to for full details, including assessment criteria and learning outcomes.

Michaelmas Term Hilary Term
BA (Mod) programme
Hilary Term
MCS programme
CSU44051 Human Factors CSU44098 Group Design Project CS7091 Industrial/Research lab Internship (Website)
CSU44081 Entrepreneurship & High Tech Venture Creation (Website) CSU44099 Final Year Project (Website)
Five options from the table below

Year 4 Module Options

The form for selecting options is available here.

CSU44001 Fuzzy Logic & Control Systems Presentation
CSU44004 Formal Verification Presentation
CSU44012 Topics in Functional Programming Presentation
CSU44031 Next Generation Networks Presentation
CSU44051 Human Factors Presentation
CSU44052 Computer Graphics Presentation
CSU44053 Computer Vision Presentation Extra Info
CSU44000 Internet Applications Presentation
CSU44061 Machine Learning Presentation
CSU44062 Advanced Computational Linguistics Presentation

CSU44051 Human Factors

5 ECTS credits, Semester 1

This module aims to provide students with an understanding of the main issues underlying the usability of systems, and the main techniques and processes for interface design and evaluation. They will also gain a basic understanding of the theories which account for human performance.

Module Description CSU44051 Blackboard

CSU44081 Entrepreneurship & High Tech Venture Creation

5 ECTS credits, Semester 1

Entrepreneurship and its contribution to the Economy & Society
The Entrepreneurial Perspective
Opportunity Recognition & Evaluation
Building & Managing your Team
Initial Funding & Financing your Growth
Developing & Executing on a Business Plan
Marketing & Promoting your Idea
Protecting Intellectual Property

Module Description CSU44081 Blackboard Module Website

CSU44098 Group Design Project

10 ECTS credits, Semester 2

The goal of this module is to promote teamwork and to allow students to use their individual skills and experiences within a development team. A key aim is to develop student’s abilities in framing design problems and working iteratively to achieve a working solution Instruction will be provided in Agile development methodologies and facilities will be provided in order to promote close collaboration between team members.

Module Description CSU44098 Blackboard

CSU44099 Final Year Project

20 ECTS credits, Semester 2

The Final Year Project is undertaken in Hilary Term by students who have elected to follow the BA (Mod) programme. The aim of the project is to integrate the theoretical and practical knowledge of the student across all of the years of their study and provide a practical demonstration of their capability in executing a challenging project.

Module Description CSU44099 Blackboard Module Website

CS7091 Industrial/Research Lab Internship

30 ECTS credits

The Internship is undertaken by students who have elected to follow the MCS programme.  The aim is to enable students to further develop an understanding of how design aspects and theoretical aspects of computer science are applied to practical problems in a real world context. For more information, please visit (and for current students a link to Submit the Internship Technical Report).

Module Description CS7091 Blackboard Module Website

CSU44001 Fuzzy Logic

5 ECTS credits, Semester 1

This course will introduce you to the exciting new field of fuzzy systems and the related topics in machine learning and the so-called deep learning neural nets. Fuzzy systems are in almost daily use: your washing machine has fuzzy controls and many of the refrigerators do too. In both cases, the machines can sense the amount of stuff (clothes or food) and adjust their operations accordingly. Equally, important is the fact that fuzzy control systems are used in managing financial markets, in operating power plants and transportation systems, and as a basis of systems that will deal help process the and almost every aspect that relies on continuous big data related issue. In short there is a fuzzy systems for monitoring and tuning. complex systems
Fuzzy logic has provided a wonderful new basis for how machines can be made to learn much like humans do especially in domains where uncertainty and approximate reasoning are the order of the day. Fuzzy logic is the bridge between the more abstract statistical machine learning and the more complex human knowledge acquisition. Fuzzy logic has been developed by computer scientists, psychologists, statisticians, and control engineers over the last 30 odd years.

Module Description CSU44001 Blackboard

CSU44004 Formal Verifications

5 ECTS credits, Semester 1

Specification languages and logics; axiomatic program semantics. Formal proof systems to verify software and system properties such as propositional, predicate and Hoare logic. Proofs by induction. Correctness proofs of functional and imperative programs.

Module Description CSU44004 Blackboard

CSU44012 Topics in Functional Programming

5 ECTS credits, Semester 1

This course builds on CS3012 which introduced the fundamental concepts of functional programming. In CS4012 we will take an in-depth look at more advanced topics in functional programming and discuss some current research directions in the field.

Module Description CSU44012 Blackboard

CSU44031 Next Generation Networks

5 ECTS credits, Semester 1

This module aims to provide both a theoretical and practical understanding of modern and next generation networking and systems concepts, principles, practices and technologies. Contemporary and emerging wired and wireless network systems are targeted.
Students will be exposed to a variety of system platforms, architectures, protocols, models and algorithms, with a strong focus on key design principles and practices e.g. performance, scalability, mobility, virtualization.
The module also aims to highlight some of the relevant ongoing research and innovation in the space taking place within Ireland and internationally.

Module Description CSU44031 Blackboard

CSU44052 Computer Graphics

5 ECTS credits, Semester 1

The objective of this module is to equip the students with the fundamental understanding of the major elements of Computer Graphics and explore related areas including geometric modelling, rendering and animation. The main focus of the module is on the mathematics and algorithms used in the synthesis of computer graphics imagery and animation, and their practical application. Students are introduced to the standard architectures of modern graphical applications including details on the underlying hardware and low-level software components common to all such systems. The module is intended to enable students to bridge the gap between these low-level fundamental, components common to all computer applications, and the high-level abstract output in most interactive graphical applications.

Students are also introduced to OpenGL, a modern high-level graphics API which is widely used for 3D Design and Visualisation, along with the industry standard modelling software, 3D Studio Max, and this software is used throughout the course to demonstrate concepts and to allow the students to develop their own 3D models, scenes and applications.

Module Description CSU44052 Blackboard

CSU44053 Computer Vision

5 ECTS credits, Semester 1

The aim of this module is to give students a firm understanding of the theory underlying the processing and interpretation of visual information and the ability to apply that understanding to ubiquitous computing and entertainment related problems. It provides them with an opportunity to apply their problem-solving skills to an area which, while it is firmly part of computer science/engineering, draws strongly from other disciplines (physics, optics, psychology). The module is based around problems so that the technology is always presented in context and during some tutorials students work in groups to design solutions to real world problems using the techniques that they have been taught. In addition, the module has a significant practical component so that students can appreciate how difficult it can be to apply the technology.

Module Description CSU44053 Blackboard

CSU44000 Internet Applications

5 ECTS credits, Semester 1

[Note that this course is running in this new format for the first time in 2019/20 and content may be adjusted slightly as the course progresses]
What is an Internet Application and how have these evolved?
Key Technologies: Javascript, Node Package Managers
Execution Environment: Client Side (Browser) and Server
Using Node.JS, NPM and support tools
Cloud Computing Architectures –SaaS, IaaS, PaaS, Serverless Computing
A simple Cloud-based Internet Application
Web Frameworks: Angular, React and Vue – The Model-View-Controller paradigm
Web Based Development – Git & Github
Database Services
Load Balancing, Scaling & Monitoring

Module Description CSU44000 Blackboard

CSU44061 Machine Learning

5 ECTS credits, Semester 1

● Machine Learning Basics (Application Areas, Challenges, Alternatives to Machine Learning)
● Machine Learning in Action (Datasets, Frameworks, Evaluation)
● Machine Learning Foundations (Statistics)
● Machine Learning Algorithms (e.g. Linear Regression, Classification, Support Vector Machines, Neural Networks)

Module Description CSU44061 Blackboard

CSU44062 Advanced Computational Linguistics

5 ECTS credits

The aim is to give a grounding in so-called unsupervised machine learning techniques which are vital to many language-processing technologies including Machine Translation, Speech Recognition and Topic Modelling. Whilst studied in these contexts, the techniques themselves are used much more widely in data mining and machine vision for example.

Module Description CS4LL5 Blackboard Module Website