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1 Year On Campus Masters Program
University College Cork UCCThe MSc in Mathematical Modelling and Machine Learning at University College Cork blends advanced mathematics with cutting‑edge machine learning to equip you with the analytical and computational skills sought by today’s tech‑driven industries. This one‑year postgraduate programme is ideal for numerate graduates who want to deepen their understanding of modelling real‑world systems and applying AI‑inspired techniques to problems in finance, engineering, data science, and beyond.
Curriculum Structure
Year 1 (Full-time MSc, 12 months — taught + dissertation):
During your year at UCC, you will engage with both core mathematical concepts and practical computational tools. You will study Numerical Methods and Applications and Scientific Computing to develop strong foundations in algorithmic problem-solving. Modules like Dynamic Machine Learning with Applications and Deep Learning introduce modern data-driven modelling techniques. Complementary courses such as Computational Techniques with Networks and Machine Learning & Statistical Analytics allow you to apply these methods to complex systems, preparing you for research or industry challenges.
Dissertation Project:
A major part of the programme is your 30-credit dissertation, where you design and implement an original modelling or machine learning project under academic supervision, combining theory and practice in a specialised area of interest.
Focus Areas
Mathematical modelling, machine learning, scientific computing, numerical methods, dynamical systems, neural networks
Learning Outcomes
Apply advanced modelling frameworks, implement machine learning algorithms, analyse complex data, use Python/R/C# for computational research, and communicate technical results effectively
Professional Alignment (Accreditation)
This MSc is an NFQ Level 9 accredited Master’s programme, quality‑assured by University College Cork’s academic governance processes
Reputation (Employability Rankings)
UCC is consistently ranked among the world’s top universities for employability and research impact, with its graduates highly regarded by Irish and international employers in technology, finance, and engineering sectors
In this MSc, learning goes beyond lectures. You’ll actively develop practical skills in programming, scientific computing, and machine learning, using real-world tools and datasets. The programme emphasizes hands-on experience in UCC’s dedicated facilities, where you work on coding, modelling, and algorithmic projects under the guidance of experienced faculty. From tutorials to independent assignments, every part of the course is designed to make sure you can confidently apply your skills to complex problems.
Here’s how this practical learning happens:
Dedicated Computer Labs: MSc students have access to computer labs equipped with all the software and tools needed to complete coursework and projects.
Industry-Relevant Software: You’ll gain hands-on experience with Python, R, C#, and machine learning frameworks such as TensorFlow, applying them directly in your modules.
Applied Assignments and Tutorials: Practical tutorials and demonstrations help you implement concepts from lectures, reinforcing your problem-solving and coding abilities.
Dissertation Project: A 30-credit dissertation gives you the chance to undertake an independent research project, combining theory with practical implementation in a real-world context.
Industry Engagement: Opportunities exist to connect research projects with industry partners, helping bridge academic learning and professional practice.
Collaborative Problem Solving: Many modules involve group work, helping you develop teamwork skills and the ability to communicate results clearly — a vital professional skill.
Students also benefit from access to UCC’s libraries, online research resources, and the university’s wider campus facilities that support postgraduate study in mathematics and machine learning.
Graduates of the MSc in Mathematical Modelling and Machine Learning from University College Cork are well prepared for rewarding careers that combine analytical thinking with cutting-edge technology. Many alumni take on roles such as Machine Learning Engineer, Data Scientist, Quantitative Analyst, or Modelling Specialist, applying their skills in sectors ranging from finance and software development to consultancy and logistics:
Career Support Services: UCC’s Careers Service provides personalised guidance for postgraduate students, including CV and interview workshops, employer events, and networking opportunities to help students secure roles in Ireland and internationally.
Graduate Employability: UCC graduates are highly sought after, with around 93 per cent of students employed or in further study within nine months of graduation, reflecting the strong demand for the skills this MSc provides.
Industry Partnerships and Opportunities: The programme has connections with industry partners such as Cadence and TOMRA, and some students may engage in internships or industry-based research projects, helping bridge academic learning and professional practice.
Long-Term Qualification Value: This degree is recognised at NFQ Level 9 and is highly valued by employers in sectors that rely on data science, machine learning, and mathematical modelling, including technology, finance, and research organisations.
Graduation Outcomes: Graduates have successfully moved into roles in banking, software development, data analytics, logistics, and consultancy, with employers ranging from major financial institutions to tech and engineering firms.
Further Academic Progression:
After completing this MSc, students may choose to pursue doctoral research (PhD) in areas such as applied mathematics, machine learning, or computational modelling at UCC or other research-intensive universities. Alternatively, students could continue with specialist postgraduate diplomas or certifications in areas like artificial intelligence, data science, or advanced statistical modelling to deepen their expertise.
Applicants should hold at least a Second Class Honours Grade I (Level 8) or equivalent in a numerate discipline such as science or engineering.Applicants should have completed university-level courses in mathematics, applied mathematics, or statistics, with knowledge of calculus, vectors, matrices, and basic statistics.Selection in case of competition will be based on primary degree results and/or an interview.Applicants from Grandes Écoles are eligible if studying a related discipline at ENSEA or EFREI and can enter the final year (M2) of their programme.English language requirement: IELTS Academic overall score of 6.5 with a minimum of 6.0 in each skill (test centre, online, and one skill retake accepted), or TOEFL iBT overall score of 90 with minimum scores of Listening 20, Reading 19, Speaking 21, and Writing 20 (Home Edition not accepted; MyBest scores accepted).India: A Bachelor of Arts, Science, Commerce, or professional bachelor’s degree with a minimum of 65%, considered equivalent to a Second Class Honours Grade I (2:1).USA: A bachelor’s degree with a minimum CGPA of 3.3 on a 4.0 scale, considered equivalent to a Second Class Honours Grade I (2:1).China: A bachelor’s degree with 80–84% from non-211/985 universities, or 75–79% from 211/985 and Double First Class universities, is considered equivalent to a Second Class Honours Grade I (2:1) for postgraduate programmes.Machine Learning EngineerData ScientistQuantitative AnalystModelling SpecialistSoftware DeveloperData AnalystOperations Research AnalystRisk AnalystBusiness Intelligence AnalystComputational ScientistResearch ScientistAI ConsultantFinancial AnalystSystems ModellerTechnical Analyst
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