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Statistical Data Science

MSc (NFQ Level 9)

This course is available through the following application route(s)

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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.

Download the UCD Science Graduate Taught Courses brochure (pdf)

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.

Contact Us

  • EU Enquiries: declan.gilheany@ucd.ie
  • Non-EU Enquiries: internationalenquiries@ucd.ie

About This Course

-    Approach data science problems in an analytical, precise and rigorous way.

-    Demonstrate in-depth knowledge of the key skills required by a practicing statistician or data scientist, including data collection methods, statistical method development, analysis of statistical output, communication of the results.

-    Demonstrate strong proficiency in computational methods, including computer programming and scientific visualization.

-    Give oral presentations of technical mathematical material at a level appropriate for the audience.

-    Model real-world problems in a statistical framework.

-    Prepare a written report on technical statistical content in clear and precise language.

-    Undertake excellent research at an appropriate level, using the statistical research skills developed throughout the programme.

-    Use the language of logic to reason correctly and make deductions.

-    Work independently and be able to pursue a research agenda.

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.

Below is a list of all modules offered for this degree in the current academic year. Click on the module to discover what you will learn in the module, how you will learn and assessment feedback profile amongst other information.

Incoming Stage 1 undergraduates can usually select an Elective in the Spring Trimester. Most continuing undergraduate students can select up to two Elective modules (10 Credits) per stage. There is also the possibility to take up to 10 extra Elective credits.

Module Type Module   Trimester Credits
Stage 1 Core Modules
 STAT30250 Advanced Predictive Analytics Spring  5
Stage 1 Core Modules
 STAT40510 Applied Statistical Modelling Spring  5
Stage 1 Core Modules
 STAT41080 Mathematical Statistics Spring  5
Stage 1 Core Modules
 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
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
 COMP40370 Data Mining Autumn  5
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
 MATH40550 Applied Matrix Theory Autumn  5
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
 STAT30340 Data Programming with R Autumn  5
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
 STAT40020 Actuarial Statistics I Autumn  5
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
 STAT40250 Survival Models Autumn  5
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
 STAT40400 Monte Carlo Inference Autumn  5
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
 STAT40680 Stochastic Models Autumn  5
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
 STAT40700 Time Series Analysis - Act App Autumn  5
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
 STAT40800 Data Prog with Python (online) Autumn  5
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
 STAT41020 Survey Sampling Autumn  5
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
 STAT41070 Bayesian Data Analysis Autumn  5
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
 COMP47750 Machine Learning with Python Autumn and Spring (separate)  5
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
 COMP40400 Bioinformatics Spring  5
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
 COMP47790 Optimisation Spring  5
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
 MEEN40670 Technical Communication Spring  5
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
 STAT30270 Statistical Machine Learning Spring  5
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
 STAT40070 Actuarial Statistics II Spring  5
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
 STAT40080 Nonparametric Statistics Spring  5
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
 STAT40150 Multivariate Analysis Spring  5
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
 STAT40970 Machine Learning & AI (online) Spring  5
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
 STAT41010 Stat Network Analysis Spring  5
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
 STAT40780 Data Prog with C (online) Summer  5
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
 STAT40830 Adv Data Prog with R (online) Summer  5
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
 STAT40840 Data Prog with SAS (online) Summer  5
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
 STAT40950 Adv Bayesian Analysis (online) Summer  5

Graduate Testimonial

Valda Murphy, Project Lead, Novartis
This MSc had a strong theoretical foundation and gave me an education in how to apply statistics. My research project inspired me to go into the area of medical statistics after graduation. The course served as a launch pad for my career in pharmaceutical statistics where I now work as a project lead, overseeing the quantitative aspects of several drugs in development.

Statistical Data Science (T387) Full Time
EU          fee per year - € 9300
nonEU    fee per year - € 22530

MSc Statistical Data Science (T388) Part Time
EU          fee per year - € 5040
nonEU    fee per year - € 14550

***Fees are subject to change

Tuition fee information is available on the UCD Fees website. Please note that 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 visit International Scholarships.

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/ 

School of Mathematics and Statistics Application Process FAQ

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

Full Time option suitable for:

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

Part Time option suitable for:

Domestic(EEA) applicants: Yes
International (Non EEA) applicants currently residing outside of the EEA Region. No


The MSc Statistical Data Science is aimed at students who have an undergraduate degree in statistics or a degree in a discipline related to statistics and with numerate skills. Examples include economics, finance, mathematics, physics, engineering, and computer science.


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General application route(s) for Irish/UK/EU applicants* for International (non-EU) applicants* to Statistical Data Science:

ROWCLASS Apply to   Application Type  
showAudience-audienceEU showAudience-audienceInt T387
Statistical Data Science
Master of Science		 Full-Time
Commencing 2024/2025 September		 Graduate Taught Apply
showAudience-audienceEU showAudience-audienceInt T388
Statistical Data Science
Master of Science		 Part-Time
Commencing 2024/2025 September		 Graduate Taught Apply
* you can change options at the top of the page
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