About This Course
Mathematical Modelling & Machine Learning
See Fees and Costs for full details.
See Requirements for full details.
Open for EU applications, check rounds closing dates under How to Apply
Non-EU Closing Date
12 September 2022
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.
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.
Further details on the modules listed above can be found in our book of modules. Any modules listed above are indicative of the current set of modules for this course but are subject to change from year to year.
You can find the full academic content for the current year of any given course in our University Calendar.
We place great emphasis on hands-on practical skills. There is a computer laboratory allocated solely for the use of MSc students. PCs are preloaded with all the required software and tools. Teaching hours, tutorials and practical demonstrations, usually take place in the morning. The rest of the time, you are expected to do exercises, assignments and generally put in the time required to acquire key skills. For online modules, students are advised to have access to a laptop/home computer with an internet connection, modern browser, word processing and spreadsheet software.
Why choose this course?
This MSc programme reflects a philosophy of cutting-edge teaching methods and pragmatism. As well as providing you with a host of abilities that are in-demand in industry, this MSc programme provides skills that are complementary to most scientific and engineering undergraduate courses.
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.
Why Choose This Course
Skills and Careers Information
Graduates with quantitative skills and expertise in self-learning algorithms are in high demand in 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.
- Candidates must have obtained at least a Second Class Honours Grade II in a primary honours degree (NFQ, Level 8) 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.
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.
Fees and Costs
The EU fee for this course is €8,130.
The Non-EU fee for this course is €18,500.
If your course required a deposit, that figure will be deducted from your second semester fee payment in January.
EU student fee payment:
Fees for EU students are payable in two equal instalments. First payment at registration in August and the second in January.
International student fee payment:
International Students can pay in two equal instalments once they have paid the appropriate deposit. The initial payment is due on registration and the balance usually by the end of January.
How can I pay?
By Credit/Debit card online or by credit transfer.
If you have any questions on fee payment please email our Fees Office at firstname.lastname@example.org .
How Do I Apply
1. Choose Course
Firstly choose your course. Applicants can apply for up to two courses under one application. Details of taught courses are available on our online prospectus.
2. Apply Online
Once you have chosen your course you can apply online at the online application portal. Applicants will need to apply before the course closing date. There is a non-refundable €50 application fee for all courses apart from the Education - Professional Master of Education - (Secondary School/Post-Primary Teacher Training) which has a €100 application fee.
Applicants for the Postgraduate Diploma in Public Health Nursing must apply on the PAC website when the programme opens for applications.
3. Gather Supporting Documents
Scanned copies of the following documents will need to be uploaded to the online application portal in support of your application. Applicants may need to produce the original documents if you are accepted onto a course and register at UCC.
- Original qualification documents listed on your application including transcripts of results from institutions other than UCC
- Any supplementary items requested for your course.
Please log into the online application portal for more details.
4. Application processing timeline
Our online application portal opens for applications for most courses in early November of each year. Check specific course details.
For courses that are in the rounds system (Irish and EU applicants), please check the rounds closing dates here.
Questions on how to apply?
Please use our web enquiry form to contact us.
The closing date for non-EU applications is 15 JuneApply Now