MSc Data & Computational Science

Graduate Taught (level 9 nfq, credits 90)

The MSc Data & Computational Science course is aimed at students who wish to gain a deep understanding of applied mathematics, statistics and computational science at the graduate level. The course will equip such students with the skills necessary to carry out research in these computationally based sciences and will prepare them well for a career either in the industry or in academia. The taught modules in the course provide a thorough grounding in the areas of applied mathematics, statistics and computational science; all students complete project work in data and computational science with the option of (supervised) research dissertation.

We expect our students to gain a thorough understanding of data and computational science at the graduate level, as well as a broad understanding of currently relevant areas of active research and to become autonomous learners and researchers capable of setting their own research agenda.

Download the UCD Science Graduate Taught Courses brochure (pdf)

For queries, please email us at dataandcomp@ucd.ie

  • The programme will equip you to solve complex scientific problems and analyse large data sets using a range of theoretical tools, from deterministic mathematical modelling to Bayesian analysis.
  • The intensive programming modules will allow you develop a range of sought-after skills in practical programming and data analytics, including applications in high-performance computing.
  • Topical application areas are offered each year, including cryptography, numerical weather prediction, and financial mathematics. The dissertation will give you further handson experience in computational science and will allow you to apply  the key theoretical and practical skills by working on a challenging research topic.

Careers & Employability

Our graduates will be suitably qualified for research at the PhD level at the interface of applied mathematics, statistics and computational science. They will be valued for their technical knowledge and research skills. Equally, our graduates will be in demand by employers for their acquired skills in data analytics and computational and statistical modelling.

Recent past graduates from this programme and other similar past programmes in the School work in firms including, ICT companies (e.g. Amazon, Meta, Geowox, Sage, Version 1, Vodafone), the financial services industry (e.g. Allianz, Aon, Deloitte, Fidelity Investments, KPMG, Permanent TSB) and other data-intensive businesses (e.g. Accenture, IBM, Intel).

Curricular information is subject to change


Full Time option suitable for:

Domestic(EEA) applicants: Yes
International (Non EEA) applicants currently residing outside of the EEA Region. Yes

The MSc in Data and Computational Science is designed for students from highly quantitative disciplines who wish to work in data analytics or computational science.

Computational science is at the crossroads between modern applied mathematics and statistics, and our programme recognizes this fact by combining aspects of both in a unique set of tailored modules including scientific computing, mathematical modelling, and data analytics.

This programme is aimed at students who wish to gain a deep understanding of applied mathematics, statistics and computational science at the graduate level. The programme will equip such students with the skills necessary to carry out research in these computationally based sciences and will prepare them well for a career either in industry or in academia. The taught modules in the programme provide a thorough grounding in the areas of applied mathematics, statistics and computational science; all students complete project work in data and computational science with the option of (supervised) research dissertation. We expect our students to gain a thorough understanding of data and computational science at the graduate level, as well as a broad understanding of currently relevant areas of active research. We expect our students to become autonomous learners and researchers capable of setting their own research agenda. Our graduates will be suitably qualified for research at the PhD level at the interface of applied mathematics, statistics and computational science. They will be valued for their technical knowledge and research skills. Equally, our graduates will be in demand by employers for their acquired skills in data analytics and computational and statistical modelling. We value students who already have a strong numerate training and are motivated to take further their knowledge in this area. We aim to provide a teaching and learning environment that develops confidence and independence through a wide variety of interactive formats, both inside and outside the classroom.

  • Analyze and interpret data, find patterns and draw conclusions
  • Apply computationally based techniques to formulate and solve problems
  • Approach problems in an analytical, precise and rigorous way
  • Demonstrate an in-depth understanding of the interface of applied mathematics, statistics and computational science.
  • Demonstrate familiarity with the areas of data and computational science currently under active research
  • Give oral presentations of technical material at a level appropriate for the audience
  • Model real-world problems in an applied mathematical or statistical framework
  • Prepare a written report on technical content in clear and precise language
  • Undertake excellent research at an appropriate level, including survey and synthesize the known literature
  • Use the language of logic to reason correctly and make deductions
  • Work independently and be able to pursue a research agenda

View All Modules Here

Core Modules in Computational Science and Mathematics

  • Optimisation in Machine Learning
  • Applied Matrix Theory
  • Uncertainty Quantification
  • Data Programming with Python
  • Data Programming with R

Core Modules in Statistics and Data Analytics

  • Probability and Statistics
  • Predictive Analytics
  • Multivariate Analysis
  • Statistical Machine Learning
  • Bayesian Analysis

Optional Modules Include

  • Machine Learning and AI
  • Scientific Computing
  • High-performance Computing
  • Mathematica for Research
  • Numerical Algorithms
  • Time Series Analysis
  • Monte Carlo Inference

Modules and topics shown are subject to change and are not guaranteed by UCD

MSc Data & Computational Science (T306) Full Time
EU          fee per year - € 8370
nonEU    fee per year - € 20440

***Fees are subject to change

Tuition fee information is available on the UCD Fees website.

UCD offers a number of graduate scholarships for full-time, self-funding international students, holding an offer of a place on a UCD graduate degree programme. For further information please see International Scholarships.

 

 

  • This programme is intended for applicants who have an Upper Second class honours degree or higher, or the international equivalent, in a highly quantitative subject such as Mathematics, Physics, Statistics, Engineering.
  • Applicants whose first language is not English must also demonstrate English language proficiency of IELTS 6.5 (no band less than 6.0 in each element), or equivalent.

School of Mathematics and Statistics Application Process FAQ

These are the minimum entry requirements – additional criteria may be requested for some programmes 

Graduate Profile

Cian O’Callaghan, Paddy Power
I would thoroughly recommend the MSc Data & Computational Science to students interested in pursuing a career/further studies in data science. The lecturers and tutors are both extremely knowledgeable and approachable. The course strikes a balance between understanding the theory behind computational and machine learning algorithms and applying this theory to real-world problems.

The following entry routes are available:

MSc Data & Computational Science FT (T306)
Duration
1 Years
Attend
Full Time
Deadline
Closed

Apply online at www.ucd.ie/apply and find the programme using the unique programme identifier: T306

Applications for the September 2023 intake will reopen in early October 2022. 

For queries, please email dataandcomp@ucd.ie