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Software Design with Artificial Intelligence – MSc

  • Location: Online

  • years: 1


Course Overview

Ireland’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 sectors 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.

International Students: We are delighted to welcome international students. Please direct all such queries to international@tus.ie

Scholarships of €1,000 to maximum of €3,000 may be awarded based on academic achievement, personal statement outlining exceptional achievements, student ambassador programme, alumni scholarship and sibling scholarship to Non-EU students who apply through International Office or Country Advisors for TUS campuses.

International TUS alumni who wish to apply for a taught master’s may qualify for €3,000 reduced fee scholarship. More information is available from the International Office.

International Applications Click Here

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Contact Details

Dr. Enda Fallon

Head of Department

Email: Enda.Fallon@tus.ie

What are the entry requirements?

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 institute policies, non-native English speakers are required to have an IELTS level of 6.5 or higher.

Course Modules

  • 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.

  • 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. The 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.

  • 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.

  • 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.

  • 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.

  • Data Visualisation

    Credits: 5

    This Module aims to give the student:

    1. A theoretical knowledge of the theory underlying data visualisation as applied to information, images, and scalar/vector/tensor representations.
    2. An in-depth knowledge of the algorithms and mathematical methods fundamental to geospatial and temporal image data
      representations
    3. A fundamental knowledge of the techniques necessary to visualise data of high dimensionality in low dimensions.
    4. The ability to apply the above knowledge/skills to problems in Machine Learning and AI.
  • 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.

  • 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.

What can you do after this programme?

According to the Forfás Vacancy Overview Report, the most difficult to fill vacancies were for the ICT sector, primarily for professional roles in software development including software developers: cloud computing, Web development database (with Oracle/SQL), Java, JavaScript, C#, and .Net the most frequently mentioned. Based on significant industrial collaboration of the Department of Computer and Software Engineering graduate of the Artificial Intelligence for Cloud Computing stream are well placed to work in these roles. According to Irelands Skills Strategy 2025 (Department of Education and Skills) there are skills shortages for professionals and associate professionals across sectors in many areas of ICT. The shortage of ICT talent is potentially significant for a number of sectors where ICT skills are needed, in particular software development. Ireland is likely to face an average increase in demand for high-level ICT skills of around 5% a year with the employment of ICT professionals anticipated to rise to just over 91,000. This skills shortage has become increasingly acute as more and more tech companies expand their operations in Ireland.”

Upon successful completion of this programme, graduates have the opportunity to complete Level 9/10 programmes here at TUS or elsewhere.