MSc in Software Design with Artificial Intelligence
Part-fundedIreland’s reputation as a centre of software excellence is unrivalled in Europe. It is home to multinational and indigenous firms generating €16 billion of exports annually. The sector’s wide-ranging activities include software development, R&D, business services and EMEA/International headquarters.
As computers become smarter, Artificial Intelligence (AI) is making strides in simulating human thinking. Creating computer systems that automatically improve with experience has many applications including robotic control, data mining, autonomous navigation, and bioinformatics.
This course provides a broad introduction to machine learning and statistical pattern recognition. Students will learn about both supervised and unsupervised learning as well as learning theory, reinforcement learning and control.
- Professionals seeking to upskill or reskill in software engineering, data analytics, machine learning and AI.
- Individuals already working in the technology sector who wish to strengthen their software development expertise and incorporate AI into their work.
- Employees in industry who require flexible, part-time learning that accommodates full-time employment.
The MSc in Software Design with AI is designed for flexible, online delivery, accommodating participants in full-time employment.
The programme is structured with live, synchronous online classes and additional academic and technical support available throughout.
Teaching combines theoretical knowledge with practical, industry-focused assignments and projects, enabling participants to develop and apply software engineering, artificial intelligence and machine learning skills in real-world contexts.
Module 1: Object Oriented Programming I
Credits: 5
This is a module using the Java programming language which is aimed at preparing the students for the Oracle Certified Associate exam (which since Java SE7, is a precursor to the Oracle Certified Professional exam).
Students with OCA certification can go through the RPL process. The methodology will be to cover the syntax and theory in a lecture, with practical coding reinforcing the theory.
Module 2: Research Methods & Professional Practice
Credits: 10
This module will equip learners to critically explore the development and completion of applied research methodologies using structured, responsible tools and actions while imbuing learners with work-ready skills for industrial practice.
Students will be introduced to the key concepts involved in research and project management and develop their understanding of the uses and relevance of the major methodologies employed.
The requirement for ethics and social responsibility are emphasised throughout, inclusive of data collection and compilation, project planning and dissemination of results.
Module 3: Applied Scripting
Credits: 5
This module provides an introduction to Python, a powerful and versatile dynamic programming language, which is used extensively in various domains of ICT.
Students will learn the basics of programming in Python and the use of functions and data structures. They will also be introduced to Python packages/modules for visualisation, regular expressions and working with dates and times.
Module 4: Data Mining and Machine Learning
Credits: 10
This module will study the principles, processes and techniques of extracting information from data with a view to improving decision making.
It will examine data mining and machine learning techniques and algorithms and their application to real world problems.
Module 5: Object Oriented Programming II
Credits : 5
This is a module, using the Java programming language, which is aimed at preparing the students for the Oracle Certified Professional exam. Initially, Generics and Collections are covered. Lambda expressions and Functional Interfaces are then detailed which leads onto the Java Stream API. Following that, File I/O, NIO.2, Threading and Concurrency are detailed. Lastly, Localisation techniques and JDBC are covered.
Module 6: Data Visualisation
Credits: 5
This Module aims to give the student:
- A theoretical knowledge of the theory underlying data visualisation as applied to information, images, and scalar/vector/tensor representations
- An in-depth knowledge of the algorithms and mathematical methods fundamental to geospatial and temporal image data representations
- A fundamental knowledge of the techniques necessary to visualise data of high dimensionality in low dimensions.
- The ability to apply the above knowledge/skills to problems in Machine Learning and AI
Module 7: Advanced Machine Learning and Neural Networks
Credits: 10
This module will build on previous modules to enhance students ability and understanding of advanced machine learning techniques. Students will be exposed to the libraries required to facilitate elicitation of semantic meaning from large scale big data corpus and will be provided with the insight to determine a good classification methodology from bad.
Students will be exposed to concepts of dimensionality reduction and aggregations to enable them to solve difficult problems by using simpler ones. Finally students will learn how to evaluate the created model and how to adopt models to different domains.
Module 8: Engineering Team Project
Credits: 10
Team based project work is a distinctive component of the applied learning process in Engineering.
The purpose of the module is to give students the opportunity to complete an applied research/development/consultancy project, or produce a research paper relevant to industry practice utilising the skills and knowledge gained throughout the programme via integration of the curriculum content.
This will require the integration of the curriculum content, whereby previous cross modular links are consolidated and the knowledge and skills accrued throughout the programme are applied to define, investigate, implement and analyse a solution to an authentic industry focused project. The learner will work as part of small focused teams on this targeted multidisciplinary project.
Students may choose to complete a research dissertation or industry based work placement.
Upon completion of the programme, you will be able to
- Evaluate, compare and contrast advanced concepts relevant to the development of cognitive software systems and the application of artificial intelligence in commercially deployed software.
- Evaluate current software development practices and emerging technologies for software and cognitive systems.
- Critically assess advances in academic and industrial research that contribute to cognitive system design.
- Evaluate business requirements and the trade-offs involved in developing complex end-to-end intelligent systems.
- Manage the development of innovative software solutions in accordance with relevant ethical and safety standards.
- Integrate software technologies and computing principles to plan and develop adaptive cognitive systems.
- Select and implement appropriate procedures, tools and standards for developing cognitive software solutions.
- Identify opportunities for future projects and improvements during software application development.
- Research and analyse state-of-the-art technologies to develop innovative solutions to real-world problems.
- Apply negotiation, conflict resolution and teamwork skills in software engineering environments, including leadership and agile development roles.
- Critically reflect on the strengths, weaknesses and opportunities for improvement in their own work.
- Evaluate personal competencies and identify further academic and professional development needs to support lifelong learning.
- Demonstrate a critical understanding of the challenges involved in designing cognitive software applications within a rapidly evolving technological environment.
The MSc in Software Design with Artificial Intelligence is assessed through a combination of continuous assessment, practical programming assignments, individual and group projects, examinations, research activities and presentations.
Assessments are designed to evaluate both theoretical knowledge and the practical application of software engineering, artificial intelligence and machine learning techniques.
Students also complete an Engineering Team Project and either a research dissertation or an approved work placement and professional practice pathway.
The programme leads to a Master of Science in Software Design with Artificial Intelligence, a Level 9 award on the National Framework of Qualifications (NFQ), awarded by Technological University of the Shannon (TUS). Successful completion requires 90 ECTS credits.
Students may also qualify for intermediate exit awards, including a Postgraduate Diploma (60 ECTS) or Postgraduate Certificate (30 ECTS), subject to the programme regulations.
Academic Eligibility
Applicants should hold a 4 year honours degree in software design or an equivalent qualification with a minimum grade of 2.1 (60%).
In line with TUS policies, non-native English speakers are required to have an IELTS level of 6.5 or higher.
Programme Fees
The fees for this programme are part-funded by Technology Ireland ICT Skillnet.
Full course fee: €6,900
Technology Ireland ICT Skillnet grant: €1,700
Subsidised course fee: €5,200*
Subsidised fees are only available to eligible applicants*.
*Funding Eligibility
Applicants must be employed by, or operating as, an eligible business engaged in economic activity in the Republic of Ireland. This includes private companies, sole traders, commercial social enterprises and eligible commercial semi-state organisations. Additional eligibility verification may be required for certain organisation types to avail of grant-aided fees. Public sector employees, non-profits, or charitable organisations that do not meet our funding criteria may apply privately for the full course fee once places are available.
Applicants who do not meet our funding criteria may be able to apply directly to the college and pay the full programme fee if there are available places.
Technological University of the Shannon (TUS)
The Technological University of the Shannon (TUS) is a multi-campus university spread across six campuses in Athlone, Limerick city, Thurles, Clonmel and Ennis. Formed on October 1st 2021 as a result of a merger between two former Institutes of Technology; Athlone Institute of Technology (AIT) and Limerick Institute of Technology (LIT), TUS is home to over 14,000 students throughout the Midlands and Midwest regions of Ireland.
By providing a healthy supply of high-quality graduates and an additional focal point for growth and innovation, TUS plays an integral part in regional development. From a national perspective, a technological university in the heart of Ireland adds a new dimension to education in the country, demonstrating a commitment to shared values like inclusivity, accessibility, and supportiveness.
TUS implements a continuous focus on partnership, innovation and staying agile through working with key stakeholders across industry and society.
If you would like to apply or to receive more information on this programme, please use the Make An Enquiry form on this page to speak directly with our programme team.
Frequently Asked Questions
The questions our team are asked most often about this programme. If your question is not answered here, make an enquiry and we will come back to you.
This programme is designed for professionals who want to develop their expertise in software engineering, machine learning and artificial intelligence. It is particularly relevant to those working in technology who want to strengthen their software development skills and apply AI within their work.
Applicants should hold a four-year honours degree in software design, or an equivalent qualification, with a minimum grade of 2.1 (60%). Applicants whose first language is not English must meet TUS’s English language requirements, which specify an IELTS score of 6.5 or higher.
Yes. The MSc in Software Design with Artificial Intelligence is delivered online over one year on a part-time basis and is designed to accommodate full-time employment. Teaching includes live online classes, practical assignments and projects, with academic and technical support available throughout the programme.
The programme combines software development with applied artificial intelligence. You will study Java through Object Oriented Programming, Python through Applied Scripting, and topics including data mining, machine learning, data visualisation and neural networks. An Engineering Team Project provides an opportunity to apply your learning to an industry-focused challenge.
Assessment combines practical programming assignments, individual and group projects, examinations, research activities and presentations. Students also complete an Engineering Team Project and either a research dissertation or an approved work placement and professional practice pathway. Successful graduates receive a Master of Science in Software Design with Artificial Intelligence from Technological University of the Shannon (TUS). This is an NFQ Level 9 qualification comprising 90 ECTS credits.
