Mathematical Modelling & Self-Learning Systems
Machine learning is an important and newly emerging technique in many areas of applied science such as applied mathematics, engineering, computer science and statistics.
In particular, machine and self-learning systems are innovative approaches to mathematical modelling which use differential equations at their foundation. A particular strength of this approach is that it ultimately allows you to design applications that can adapt to a changing environment. This is a new and rapidly developing area at the interface between applied mathematics and machine learning.
The primary aim of our Mathematical Modelling programme at UCC is to provide you with training in the use and development of modern numerical methods and machine-learning software. You will develop and apply new skills to real-world problems using mathematical ideas and techniques together with software tailored for complex networks and self-learning systems. While there is a strong focus on modern applications, our graduates will gain in-demand skills in mathematical modelling, problem-solving, scientific computing, dynamic machine learning, complex networks and communication of mathematical ideas to a non-technical audience.
We also teach general hands-on skills such as mathematical typesetting, mathematical writing, desktop and web-based mathematical software development, and the use of computer languages and packages such as C#, R, Python and TensorFlow – all of which are highly prized by employers in this field.
Why Choose This Course
This MSc programme reflects a philosophy of cutting-edge teaching methods and pragmatism. We believe that our programme opens up multiple new possibilities for our graduates; it will provide you with a skill set that will make you stand out from the crowd in your original field of study. The final project is an excellent opportunity for you to showcase your abilities to future employers or to undertake a detailed study in a new area of interest. The course is extremely flexible in helping you realise your ambitions.
We encourage innovative teaching and learning practices at UCC and this is embodied in the online delivery of this programme. Our accessible learning approach reflects our commitment to the Connected Curriculum where we emphasise the connection between students, learning, research and leadership through our vision for a Connected University. Our staff from the School of Mathematical Sciences have made significant contributions to their discipline and will support you in making meaningful connections across the breadth of mathematics, statistics and computer technology.
Candidates must have obtained at least a 2.2 honours degree or equivalent in a numerate discipline (i.e., commensurate with science or engineering programmes).
Candidates are expected to have taken courses in mathematics, applied mathematics or statistics at university level, and be familiar with calculus, vectors, matrices and elementary statistics. They are expected to have sufficient background in university-level mathematics as assessed by the course coordinator. In the case of competition for places selection will be made on the basis of primary degree results and/or interview. For online modules, students are advised to have access to a laptop/home computer with internet connection, modern browser, word processing and spreadsheet software.
Candidates from Grandes Écoles Colleges are also eligible to apply if they are studying a cognate discipline in an ENSEA or EFREI Graduate School and are eligible to enter the final year (M2) of their programme.
All candidates must ultimately be approved by the director of the MSc (Mathematical Modelling and Self-Learning Systems) programme.
If you are applying with Qualifications obtained outside Ireland and you wish to verify if you meet the minimum academic and English language requirements for this programme please view the grades comparison table by country and for details of recognised English language tests.
Non-EU candidates are expected to have educational qualifications of a standard equivalent to Irish university primary degree level. In addition, where such candidates are non-native speakers of the English language they must satisfy the university of their competency in the English language. To verify if you meet the minimum academic requirements for this programme please visit our qualification comparison pages.
For more detailed entry requirement information please refer to the International website .
English Language Requirements
Applicants that are non-native speakers of the English language must meet the university approved English language requirements available here.
For applicants with qualifications completed outside of Ireland
Applicants must meet the required entry academic grade, equivalent to Irish requirements, please find our grades comparison by country here.
For full details of the non-EU application procedure please visit our how to apply pages for international students. In UCC, we use the term programme and course interchangeably to describe what a person has registered to study in UCC and its constituent colleges, schools, and departments.
Not all courses are open to international/non-EU applicants, please check the fact file above.
For more information please contact the International Office.
This is a full-time, blended learning programme running for 12 months from the date of first registration for the programme.
Students take 90 credits as follows:
AM6004: Numerical Methods and Applications (5 credits)
AM6005: Nonlinear Dynamics (5 credits)
AM6007: Scientific Computing with Numerical Examples (10 credits)
AM6015: Computational Techniques with Networks (5 credits)
AM6016: Dynamic Machine Learning with Applications (5 credits)
AM6017: Complex and Neural Networks (5 credits)
AM6020: Open Source Infrastructure for Mathematical Modelling and Big Data Applications (5 credits)
CS6421 Deep Learning (5 credits)
EE6024 Engineering machine Learning Solutions (5 credits)
ST4060: Statistical Methods for Machine Learning I (5 credits)**
ST4061: Statistical Methods for Machine Learning II (5 credits)**
Students who have taken any of the above modules in a previous degree must select alternative modules (subject to availability and timetabling) in consultation with the Programme Coordinator.
AM6018: Dissertation in Mathematical Modelling and Machine Learning (30 credits)
Please see the University Calendar (Mathematical Modelling & Self-Learning Systems) for further course information.
1 year full-time
Start Date 7 September 2020
Post Course Info
Skills and Careers Information
Graduates with quantitative skills and expertise in self-learning algorithms are in high demand in the industry according to the Government Expert Group on Future Skills Needs (EGFSN). Demand for these skills is projected to rise over the coming years not just in Ireland but in the EU and globally. Graduates from a similar MSc have secured jobs in the following areas: banking, financial trading, consultancy, online gambling firms, software development, logistics, data analysis, and with companies such as AIB, McAfee, Fexco, DeCare Systems, MpStor, the Tyndall Institute, Matchbook.com, First Derivatives, and KPMG.