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Statistical Data Science

MSc (NFQ Level 9)
Scholarships Available

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

Duration:
1 Year
Attendance:
Full Time
Delivery:
On Campus
NFQ Level:
9 (90 credits)
Level:
Graduate Taught
Award:
Master of Science
Next Intake:
September
Country Specific Entry Requirements:
Visit the UCD Global Undergraduate Entry Requirements webpage.
Other School Leaving Requirements:
See www.ucd.ie/admissions
Curricular information is subject to change.

Duration:
2 Years
Attendance:
Part-Time
Delivery:
On Campus
NFQ Level:
9 (90 credits)
Level:
Graduate Taught
Award:
Master of Science
Next Intake:
September
Country Specific Entry Requirements:
Visit the UCD Global Undergraduate Entry Requirements webpage.
Other School Leaving Requirements:
See www.ucd.ie/admissions
Curricular information is subject to change.

Apply Now

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 data science. 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 for those interested in pursuing a subsequent PhD in related areas. It may not be suitable for applicants with a significant background in statistics.

The course 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 may have the opportunity to take a supervised research module or internship where they develop a 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.

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.

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
 STAT20230 Modern Regression Analysis Autumn  5
Stage 1 Core Modules
 STAT41190 Modern Statistical Data Analysis Autumn  5
Stage 1 Core Modules
 STAT41200 Foundations of Statistics Autumn  5
Stage 1 Core Modules
 STAT30250 Advanced Predictive Analytics Spring  5
Stage 1 Core Modules
 STAT41080 Mathematical Statistics Spring  5
Stage 1 Core Modules
 STAT41180 Applied Stat Data Analysis Spring  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 ACM40290 Numerical Algorithms Autumn  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 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 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 MEEN40820 Technical Comms (Online) Autumn  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT30340 Data Programming with R (Blended) Autumn  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 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 6 of:
Select a minimum of 30 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 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT41020 Survey Sampling Autumn  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 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 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 ECON42720 Causal Inference & Policy Evaluation Spring  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 MEEN40670 Technical Communication Spring  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 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 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT40080 Nonparametric Statistics Spring  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT40150 Multivariate Analysis Spring  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 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 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT41120 Machine Learning and AI Spring  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT40740 Multivariate Analysis (Online) Summer  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT40810 Stochastic Models (online) Summer  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 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 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT40950 Adv Bayesian Analysis (online) Summer  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT40960 Stat Network Analysis (online) Summer  5
Stage 1 Options - A) Min 6 of:
Select a minimum of 30 credits from the following list of Option modules in consultation with your course coordinator
 STAT41210 Intro to SQL Databases(Online) Summer  5
Stage 1 Options - B)1 of:
Students must select one of these core modules in consulation with the Programme Director. Please note that STAT40540 is an internship module
 STAT40540 Dissertation Summer  30
Stage 1 Options - B)1 of:
Students must select one of these core modules in consulation with the Programme Director. Please note that STAT40540 is an internship module
 STAT41170 Projects in Statistics Summer  15
Stage 1 Options - B)1 of:
Students must select one of these core modules in consulation with the Programme Director. Please note that STAT40540 is an internship module
 STAT41220 Dissertation - Statistical Data Science Summer  30

Rodger Clery, Graduate
As someone with an interest in statistics, I really enjoyed the MSc Statistical Data Science. I found the topics covered to be very interesting, and I liked how the modules focused on the application of techniques. There was a lot of flexibility when choosing modules, due to the small number of core modules, allowing me to focus on subjects that were most of interest to me. The presentation-based modules were a particular highlight for me as I felt they dramatically improved both my ability to deliver presentations and write reports on my work, skills which are relevant in both industry and academia. As part of my thesis, I got the opportunity to undertake a paid internship at Novartis. During this time, I got relevant work experience, expanded my network, and applied what I had learned in a real-world setting. I was pleasantly surprised by how well the course had equipped me for the working world, and how many of the techniques I had learned were applicable to my job.

Statistical Data Science (T387) Full Time
EU          fee per year - € 9720
nonEU    fee per year - € 27720

MSc Statistical Data Science (T388) Part Time
EU          fee per year - € 5275
nonEU    fee per year - € 14755

***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 course is intended for applicants with a degree in a numerate subject. An upper second class honours or international equivalent
is required.

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 

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.

Full Time option suitable for:

Domestic(EEA) applicants: Yes
International (Non EU) applicants: Yes

Part Time option suitable for:

Domestic(EEA) applicants: Yes
International (Non EEA) applicants: No


The MSc Statistical Data Science is aimed at students who have an undergraduate degree in any numerate subject. This programme has a strong focus on the mathematical and statistical aspects of data 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
showAudience-audienceEU showAudience-audienceInt
T387
Statistical Data Science
Master of Science

Full-Time
Commencing September 2026
Graduate Taught
Closed
showAudience-audienceEU showAudience-audienceInt
T388
Statistical Data Science
Master of Science

Part-Time
Commencing September 2026
Graduate Taught
Not available to International applicantsClosed
showAudience-audienceEU showAudience-audienceInt
T387
Statistical Data Science
Master of Science

Full-Time
Commencing September 2027
Graduate Taught
Opens 01 Oct 2026
showAudience-audienceEU showAudience-audienceInt
T388
Statistical Data Science
Master of Science

Part-Time
Commencing September 2027
Graduate Taught
Not available to International applicantsOpens 01 Oct 2026
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