Data Science and Statistical Learning MSc
Limerick, Ireland
DURATION
1 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
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EARLIEST START DATE
Sep 2025
TUITION FEES
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STUDY FORMAT
On-Campus
Introduction
The course modules have been carefully developed with a focus on statistics and computing to assist students in developing skills in statistical modelling, data visualisation and interpretation, database management, statistical programming, network analysis and predictive algorithms. Students are also provided with an opportunity to specialise in more applied elements of data science through the undertaking of a research project and dissertation. The objectives of the course are:
- To enable graduates of quantitative disciplines to redirect their training towards the rapidly growing field of data science.
- To provide students with a fundamental grounding in the key skills of data science including; data manipulation, data interrogation and visualisation, statistical modelling, and scientific computation.
- To provide students with technical research and presentation experience, through the undertaking of a research project and writing of an MSc dissertation.
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Admissions
Scholarships and Funding
Several scholarship options are available. Please check the university website for more information.
Curriculum
Autumn Semester
- Statistical Inference for Data Science
- Fundamentals of Statistical Modelling
- Scientific Computation
- Database Systems in Practice
- Text Analytics and Natural Language Processing
Spring Semester
- Statistical Learning
- Quantitative Research Methods for Science, Engineering and Technology
- Networks and Complex Systems
- Applied Big Data and Visualisation
- Artificial Intelligence and Machine Learning
Summer Semester
- Research Project Students will specialise their dissertation studies in one of the three sub-disciplines: Mathematics and Statistics, Electronic and Computer Engineering, or Computer Science and Information Systems
Program Outcome
Qualification - NFQ Level 9 Minor Award
Program Tuition Fee
Career Opportunities
Data science skills are some of the most highly sought after by employers both nationally and internationally. There is a rapidly increasing demand for individuals with strong proficiencies in data analysis and scientific computation. Examples of potential fields of employment (and employers) include:
- ICT (e.g. Apple, Facebook, Google, Linkedin, Microsoft, Tenable, TikTok)
- Financial services and management consulting (e.g. Accenture, AIB, Aon, Bank of Ireland, Deloitte, EY, KPMG, PWC, Zurich)
- Manufacturing and pharmaceuticals (e.g. Abbott, Eli Lilly, Glanbia, Johnson & Johnson, Regeneron)
- Research and development roles in a wide variety of applied fields, as well as strengthening applicant candidacy for application to PhD programmes
Program Admission Requirements
Show your commitment and readiness for Grad school by taking the GRE - the most broadly accepted exam for graduate programs internationally.