Statistical Data Science

The goal of the UCD MSc Statistical Data Science is to train the new generation of data scientists, by empowering them with a broad range of foundational and applied skills in statistics and machine learning. On completion of the MSc Statistical Data Science, you will be able to demonstrate in-depth understanding of statistical concepts, apply advanced statistical reasoning, techniques and models in the analysis of real data and employ technical computing skills. The MSc Statistical Data Science is ideal for students interested in data science careers in industry, business, government, or to those interested in pursuing a subsequent PhD in statistics or in related areas.



The programme trains students in both applied and theoretical statistical data science, and prepares them well for a career as research data scientists. A wide variety of taught modules provides a thorough grounding in statistics and machine learning. Compulsory modules are intended to ensure that all students have appropriate statistical knowledge and experience, while optional modules provide depth and exposure to the diverse range of statistical methods and applications. In addition, students take a supervised research module where they develop an individual project that addresses a present-day statistical problem.



In this programme, you will learn how to design, use and interpret a variety of statistical modelling tools, combining the fundamental theory of statistics with modern computational techniques. The programme is underpinned by several thematic areas:



- Data Science: in several of our modules, you will tackle on modern real-world problems, using a variety of advanced techniques that are common in statistics and machine learning. Modules examples: Statistical Machine Learning, Data Mining, Advanced Predictive Analytics.



- Computing: you will learn how to design and implement efficient algorithms, through various data science programming languages and software that are commonly used in industry and research. Modules examples: Data Programming, Optimisation, Machine Learning with Python.



- Fundamental theory: you will cover the fundamental aspects of mathematical statistics and learn how this is used in data science to develop new methods and concepts. Modules examples: Mathematical Statistics, Multivariate Analysis, Stochastic Models.



- Communication: you will learn how to study and interpret statistical analyses, and also how to effectively communicate your conclusions. Modules examples: Technical Communication, Applied Statistical Modelling, Dissertation.

You will have the flexibility to choose your modules from a wide range of statistics topics. In addition, you will take a final dissertation module which provides you with the chance to work extensively and individually on a statistical problem, with potential industry applications or research novelty.

Stage 1 Core Modules

STAT30250 Advanced Predictive Analytics Spring 5

STAT40510 Applied Statistical Modelling Spring 5

STAT41080 Mathematical Statistics Spring 5

STAT40710 Dissertation Summer 25



Stage 1 Options - A) Min 10 of:

Select a minimum of 50 credits from the following list of Option modules in consultation with your course coordinator

ACM40290 Numerical Algorithms Autumn 5

COMP40370 Data Mining Autumn 5

MATH40550 Applied Matrix Theory Autumn 5

STAT30340 Data Programming with R Autumn 5

STAT40020 Actuarial Statistics I Autumn 5

STAT40250 Survival Models Autumn 5

STAT40400 Monte Carlo Inference Autumn 5

STAT40680 Stochastic Models Autumn 5

STAT40700 Time Series Analysis - Act App Autumn 5

STAT40800 Data Prog with Python (online) Autumn 5

STAT41020 Survey Sampling Autumn 5

STAT41070 Bayesian Data Analysis Autumn 5

COMP47750 Machine Learning with Python Autumn and Spring (separate) 5

COMP40400 Bioinformatics Spring 5

COMP47790 Optimisation Spring 5

MEEN40670 Technical Communication Spring 5

STAT30270 Statistical Machine Learning Spring 5

STAT40070 Actuarial Statistics II Spring 5

STAT40080 Nonparametric Statistics Spring 5

STAT40150 Multivariate Analysis Spring 5

STAT40970 Machine Learning & AI (online) Spring 5

STAT41010 Stat Network Analysis Spring 5

STAT40780 Data Prog with C (online) Summer 5

STAT40830 Adv Data Prog with R (online) Summer 5

STAT40840 Data Prog with SAS (online) Summer 5

STAT40950 Adv Bayesian Analysis (online) Summer 5

This programme is intended for applicants who hold a degree in Statistics or a cognate subject area. An upper second class honours, or international equivalent is required.



Those who have been awarded an upper second class honours or higher in the Higher Diploma in Statistics are eligible for the programme.



Alternatively students may qualify for enrolment for the four semester MA in Statistics which brings them to the same level as the MSc in Statistical Data Science.



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.



Students meeting the programme’s academic entry requirements but not the English language requirements, may enter the programme upon successful completion of UCD’s Pre-Sessional or International Pre-Master’s Pathway programmes. Please see the following link for further information http://www.ucd.ie/alc/programmes/pathways/



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



You may be eligible for Recognition of Prior Learning (RPL), as UCD recognises formal, informal, and/or experiential learning. RPL may be awarded to gain Admission and/or credit exemptions on a programme. Please visit the UCD Registry RPL web page for further information. Any exceptions are also listed on this webpage. https://tinyurl.com/2ae2ffax

1 year full-time (T387), 2 years part-time (T388). Delivery: On Campus.

Next Intake: September 2025.

Career & Graduate Study Opportunities The MSc Statistical Data Science graduates typically pursue careers related to data science as research data scientists, data analysts, and data engineers. As the demand for data scientists is growing, career opportunities exist in a variety of industries including pharmaceutical companies, banking, finance, government departments, risk management and the IT sector. A number of past students also embarked on a career in academia by proceeding to study for a PhD in statistics, data science, or related fields. MSc Statistical Data Science graduates are currently working for companies such as Google, Western Union, AIB, Norbrook, Ernst & Young, Novartis, Deloitte, Meta and Eaton. Demand for our MSc Statistical Data Science graduates continues to be very strong both in Ireland and abroad.