Programme Overview:
- Duration:
- 16 Months / 32 Months
- Attendance:
- Full Time / Part Time
- Mode of Delivery:
- Face-to-Face
- Next Intake:
- 2024/2025 September
- Contact Name:
- Contact Number:
- +353(0)1 716 2580
- Fees:
- Fee Information
The goal of the MA Statistics is to train the new generation of data scientists, by empowering them with a broad range of skills in statistics and machine learning. Once completed, the MA Statistics brings students to the same level as the MSc Statistical Data Science: the degrees are equivalent. However, differently from the 1-year MSc Statistical Data Science, the MA Statistics is 16 months long, and it includes several fundamental statistics modules in its core structure. These modules cover the fundamentals of statistics and data science, and prepare students for more advanced modules.
The MA Statistics programme is aimed at students who have an undergraduate degree in a discipline with numerate skills, and who have covered some basic topics of statistics.
The MA Statistics is an EMOS (European Master in Official Statistics) labelled programme, which means that some students may have the opportunity to take modules and a project on official statistics, and potentially receive the EMOS certification of their degree. The EMOS MA Statistics also includes a research module, which is provided in the form of an internship at an institution whose work involves official statistics. The MA Statistics is the only EMOS accredited programme in Ireland and it is ideal for students that are interested in pursuing a career in official statistics, in Ireland or abroad.
The MA Statistics is ideal for students interested in data science careers in industry, business, government, and to those interested in pursuing a subsequent PhD in statistics or other areas related to data science.
Download the UCD Science Graduate Taught Courses brochure (pdf)
On successful completion of the programme, students 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.
Career opportunities exist in a variety of industries including pharmaceutical companies, banking, finance, government departments, risk management and the IT sector. Some past students embarked on a career in academia by proceeding to study for a PhD.
Graduates are currently working for companies such as Google, Western Union, AIB, Norbrook, Ernst & Young, Novartis, Deloitte, Meta and Eaton. Demand for our Statistics graduates continues to be strong both in Ireland and abroad.
Curricular information is subject to change
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 MA Statistics is aimed at students who have an undergraduate degree in a discipline with numerate skills, and a basic knowledge of probability and statistics.
This programme is aimed at students who have an undergraduate numerate degree with a basic background of statistics, and who wish to gain a deeper understanding of statistics and of its role in data science. The programme trains students in both applied and theoretical statistics, and prepares them well for a career either in industry or in academia. A wide variety of taught modules provide a thorough grounding in statistics; in addition, students take a supervised research module to develop an individual research project to address a present-day statistical problem. We train our students to become autonomous learners and researchers capable of setting their own research agenda. They will be capable of solving relevant problems in the language of statistics. Our graduates are in demand by employers and academic research institutes for their ability to use the tools they have learned to explain, describe and predict. We value students who are motivated to find the underlying causes and reasons for observations and patterns. We aim to provide a teaching and learning environment that develops confidence and independence through a wide variety of interactive formats, both inside and outside the classroom.
- 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.
There are 120 credits of work to do spread over four semesters including nine 5-credit modules (45 credits) from the Higher Diploma programme
Students must take all Core modules in addition to the dissertation in order to complete the programme.
MA Statistics (F043) Full Time
EU fee per year - € 12500
nonEU fee per year - € 22530
MA Statistics (F044) Part Time
EU fee per year - € 4280
nonEU fee per year - € 7520
***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 see International Scholarships.
School of Mathematics and Statistics Application Process FAQ
These are the minimum entry requirements – additional criteria may be requested for some programmes
Faculty Profile
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.
The following entry routes are available:
* Courses will remain open until such time as all places have been filled, therefore early application is advised