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Statistical Data Science

MA (NFQ Level 9)

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

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The MA Statistical Data Science is aimed at graduates from numerate subjects with good statistical and mathematical training, or who have completed the Higher Diploma Statistics or the Graduate Certificate Statistics. The MA Statistical Data Science brings the students to the same level as the MSc Statistical Data Science: once completed, the degrees are equivalent. However, in contrast to the MSc Statistical Data Science, the MA Statistical Data Science is 16 months long, and it includes several foundational statistics modules in its core structure. These modules cover the fundamentals of statistics, machine learning, and data science, and prepare the students for more advanced modules. In addition, students take a supervised research module where they develop an individual project that addresses a present-day statistical problem. The programme trains students in both applied and theoretical statistical data science, and prepares them well for a career as research data scientists.

The MA Statistical Data Science is an EMOS (European Master in Official Statistics) labelled programme, which means that some students may choose to take modules and an individual project on official statistics, and potentially receive the EMOS certification of their degree. The EMOS MA Statistical Data Science programme also includes an internship at an Irish public institution that deals with official statistics. The EMOS MA Statistical Data Science provides an excellent opportunity to get involved and pursue a career in official statistics in Ireland or abroad, and there is no comparable programme in Ireland or the UK.

Contact Us

  • EU Enquiries: smspostgrads@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.

Career prospects on completion of the Statistical Data Science are equivalent to those of the MSc Statistical Data Science and 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. 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 MA in 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
 STAT30270 Statistical Machine Learning Spring  5
Stage 1 Core Modules
 STAT40510 Applied Statistical Modelling Spring  5
Stage 1 Core Modules
 STAT40770 Adv Pred Analytics (online) Spring  5
Stage 1 Core Modules
 STAT40710 Dissertation Summer  25
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 ACM40290 Numerical Algorithms Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 COMP40370 Data Mining Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 COMP47790 Optimisation Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 MATH40550 Applied Matrix Theory Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT30340 Data Programming with R (Blended) Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40020 Actuarial Statistics I Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40110 Design of Experiments Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40250 Survival Models Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40400 Monte Carlo Inference Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40680 Stochastic Models Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40700 Time Series Analysis - Act App Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40800 Data Prog with Python (online) Autumn  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 COMP47750 Machine Learning with Python Autumn and Spring (separate)  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 COMP40400 Bioinformatics Spring  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 MEEN40670 Technical Communication Spring  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40070 Actuarial Statistics II Spring  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40080 Nonparametric Statistics Spring  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40150 Multivariate Analysis Spring  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT41080 Mathematical Statistics Spring  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT41120 Machine Learning and AI Spring  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40830 Adv Data Prog with R (online) Summer  5
Stage 1 Options - D) Min 14 of:
Please note - you require a minimum of 70 credits of Option modules to complete the programme.
 STAT40950 Adv Bayesian Analysis (online) Summer  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 ACM40290 Numerical Algorithms Autumn  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 COMP40370 Data Mining Autumn  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 MATH40550 Applied Matrix Theory Autumn  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 STAT30340 Data Programming with R (Blended) Autumn  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 STAT40020 Actuarial Statistics I Autumn  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 STAT40250 Survival Models Autumn  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 STAT40400 Monte Carlo Inference Autumn  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 STAT40800 Data Prog with Python (online) Autumn  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 STAT41070 Bayesian Data Analysis Autumn  5
Stage 1 Options - E)8 of:
Year 2 Option Modules
 COMP47750 Machine Learning with Python Autumn and Spring (separate)  5

Module list will appear here when available.


    

Dr Michelle Carey, UCD School of Mathematics and Statistics

The ever-increasing rise of automated measurements allows us an unprecedented view of the world around us. Traditional statistical methodology is challenged by this more complex and high-dimensional data. My research advances statistical and numerical methods for the analysis of high-dimensional functional data in climatology, finance and medicine.

Statistical Data Science (F261) Full Time
EU          fee per year - € 12810
nonEU    fee per year - € 22530

Statistical Data Science (F262) Part Time
EU          fee per year - € 4390
nonEU    fee per year - € 7520

***Fees are subject to change

  • This programme is intended for applicants with a degree in Mathematics, Economics, Finance, certain Engineering degrees or similar quantitative disciplines where statistics has formed some component of the degree. An upper second class honours, or international equivalent is required.
  • Applicants who do not meet these requirements but can demonstrate an interest and ability in statistics may be considered.
  • Alternatively students may qualify for enrolment to the Higher Diploma Statistics from which they can gain entry to the 1-year MSc in Statistics.
  • 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 

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


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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
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F261
Statistical Data Science
Master of Arts

Full-Time
Commencing September 2025
Graduate Taught
Apply
showAudience-audienceEU showAudience-audienceInt
F262
Statistical Data Science
Master of Arts

Part-Time
Commencing September 2025
Graduate Taught
Not available to International applicantsApply
* you can change options at the top of the page
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