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Computer Science—Adaptive Cybersecurity (MSc)
Course Overview
Cybersecurity is one of the most exciting and fastest growing areas of the ICT industry. It is a domain of enormous economic and societal importance, as it is aimed to protect citizens, businesses, and organisations against increasingly complex, damaging, and sophisticated attacks.
This increasing complexity and level of sophistication requires new means of attack detection, protection, and mitigation, which are addressed by this innovative new programme, the MSc in Computer Science (Adaptive Cybersecurity) offered by the University of Galway.
Adaptive cybersecurity incorporates state-of-the-art advanced dynamic cybersecurity techniques, algorithms, and frameworks to efficiently protect and mitigate systems and organisations against new emerging threats.
This 12-month full-time programme provides cutting edge technical training and research opportunities in the emerging area of AI-driven and data analytics-driven cybersecurity. It is a unique offering that is only matched by a small number of European and US-based Universities and builds on the vast research experience and technical skills of renowned, interdisciplinary experts based in the School of Computer Science, University of Galway.
This programme is aimed at graduates with a primary qualification and / or extensive industry experience in Computer Science or related subject area. It is not a conversion programme but expects students to already be at a very high standard regarding their Computer Science education.
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You may also be interested in one of our other School of Computer Science postgraduate programmes.
Applications and Selections
Applications are made online via the University of Galway Postgraduate Applications System.
Please visit Supporting Documents website for detail on what you need to include with your online application.
Who Teaches this Course
- Dr Malika Bendechache
Data Science Institute
University of Galway
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INFORMATION TECHNOLOGY
SCHOOL OF ENGINEERING
& INFORMATICS
IT BUILDING
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Computer Science Building
University of Galway
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Computer Science
University of Galway
Galway
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IT Building 441
University of Galway
Galway
Ireland
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Requirements and Assessment
Key Facts
Entry Requirements
- This MSc is targeted at high-performing graduates of Level 8 computer science programmes, or Level 8 science/engineering programmes that offer sufficient training in computing.
- The minimum academic requirement for entry to the programme is a First Class Honours (or equivalent) from a recognised university or third-level college. However, a good Second Class Honours (or equivalent) can be deemed sufficient on the recommendation of the Programme Director.
- English language proficiency
Overall, entry to the MSc Artificial Intelligence requires a minimum IELTS score of 6.5 overall, 6.5 in Writing and no less than 6.0 in any other band. TOEFL: Overall 88, Listening 12–19, Speaking 18–19, Writing 24–26, Reading 13–18. PTE: Overall 61, Writing 61, all other bands no less than 50.
- Applicants are required to submit a personal statement outlining:
- A summary of your primary degree and its relevance for a successful completion of this programme. We strongly encourage an evidence based approach to highlighting your academic accomplishments.
- A summary of your previous capstone projects (e.g., undergraduate final year projects) including an outline of your exact contribution there. We strongly encourage an evidence based approach to outlining your existing technical skills and experience
- Please upload a current C.V.
Additional Requirements
Recognition of Prior Learning (RPL)
Duration
1 year, full-time
Next start date
September 2025
A Level Grades ()
Average intake
25
QQI/FET FETAC Entry Routes
Closing Date
No set closing date. Offers made on a continuous basis
NFQ level
Mode of study
ECTS weighting
90
Award
CAO
Course code
1ACS1
Course Outline
Students will collect 90 ECTS during 12 months of full-time studies. The programme covers over two semesters many complementary areas of Cybersecurity, Artificial Intelligence, and Data Analytics, including Intrusion Detection and Malware Analysis, Secure DevOps, Ethics & Data Privacy, Deep Learning, Case Studies in Cybersecurity Analytics, Autonomous Agents and Multi-Agent Systems. Further on, students reinforce their newly gained skills in a project that is completed during the summer.
During semester 1 students will focus on foundation topics comprising of 5 core modules and one elective module (30 ECTS in total) as follows:
Module Code | Module Name | Core/Elective |
CT5165 |
Principles of Machine Learning |
Core |
CT5189 | Introduction to Cybersecurity | Core |
CT5191 | Network Security & Cryptography | Core |
CT5190 | Societal Impact of AI and Cybersecurity | Core |
CT5132 |
Prog. and Tools for AI | Core |
CT5141 | Optimisation | Elective |
CT5120 | Natural Language Processing 1 | Elective |
CT561 | System Modelling and Simulation | Elective |
CT5105 | Tools & Techniques for Large Scale DA | Elective |
During semester 2 advanced topical areas will be covered, again comprising of 5 core modules and one elective module (30 ECTS in total) as follows:
Module Code | Module Name | Core/Elective |
CT5133 |
Deep Learning |
Core |
CT5100 | Data Visualisation | Core |
CT5192 | Secure DevOps | Core |
CT5193 | Case Studies in Cybersecurity Analytics | Core |
CT5194 |
Malware and Intrusion Detection | Core |
CT5134 | Agents, Multi-Agent Systems and Reinforcement Learning | Elective |
CT5121 | Advanced Topics in NLP | Elective |
CT5113 | Web & Network Science | Elective |
CT5187 | Knowledge Representation | Elective |
Lectures are complemented by weekly labs and tutorials. Assignment work will typically provide 30% of a subject’s overall mark, while the remaining 70% are covered by an end-of-term examination.
Following the semester 2 examination period students will work on a 30 ECTS, 3-month research / capstone project (CT5195), where they showcase their newly gained skills by applying a variety of artificial intelligence and data analytic techniques to solve a real-world cybersecurity problem.
Why Choose This Course?
Career Opportunities
The high global demand in cybersecurity experts is being reflected in a range of career options for example as network security architect, cybersecurity operations analyst or information security analyst.
While our graduates can compete for such jobs, the programme, in particular, will cater for the demand stemming from emerging R&D career paths in cybersecurity that have a strong focus on machine learning and data analytics. These include positions such as an AI security controls architect, cybersecurity data analytics engineer, or cyber intelligence analyst.
Who’s Suited to This Course
Learning Outcomes
Transferable Skills Employers Value
- Develop skills needed for sustained critical reflection.
- Enhance skills in the area of problem solving through engagement with difficult organisational and technical (cyber-) security questions.
- Enhance students’ skills in research, communication, and innovative thinking.
- Identify the general principles that connect problems and thereby evaluate the strengths and weaknesses of cybersecurity measures in an organisation. [Critical Reasoning]
- Conduct structured, educated and result-driven research on a known threat, as well as the ability to perceive potential future threats and their mitigations. [Analytical Skills]
- Communicate difficult ideas in a clear and persuasive manner, while listening to problems/ideas/proposals, and understanding and providing different points of view. [Communication Skills]
- Look at problems from diverse points of view. [Design and Planning Skills]
- Identify a security problem and formulated questions relevant to clarifying the threat(s)/issue(s). [Research and Investigation Skills]
Work Placement
Study Abroad
Related Student Organisations
Course Fees
Fees: EU
Fees: Tuition
Fees: Student levy
Fees: Non EU
For 25/26 entrants, where the course duration is greater than 1 year, there is an inflationary increase approved of 3.4% per annum for continuing years fees.
Postgraduate students in receipt of a SUSI grant – please note an F4 grant is where SUSI will pay €4,000 towards your tuition (2025/26). You will be liable for the remainder of the total fee. A P1 grant is where SUSI will pay tuition up to a maximum of €6,270. SUSI will not cover the student levy of €140.
Note to non-EU students: learn about the 24-month Stayback Visa here.
Find out More
MSc (Adaptive Cybersecurity) Programme Administrator,
School of Computer Science,
College of Science and Engineering,
University of Galway.
T: +353 91 493 835
E: MScCS-ACS@universityofgalway.ie
www.cs.universityofgalway.ie