Course Details
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Brief Description
The MSc in Data Science and Statistical Learning provides an exciting opportunity for students with a quantitative background to specialise in the rapidly expanding field of data science, with an emphasis on statistical perspectives.
The course modules have been carefully developed with a focus on statistics and computing to assist students in developing skills in statistical modelling, data visualisation and interpretation, database management, statistical programming, network analysis and predictive algorithms. Students are also provided with an opportunity to specialise in more applied elements of data science through the undertaking of a research project and dissertation. The objectives of the course are:
- To enable graduates of quantitative disciplines to redirect their training towards the rapidly growing field of data science.
- To provide students with a fundamental grounding in the key skills of data science including; data manipulation, data interrogation and visualisation, statistical modelling, and scientific computation.
- To provide students with technical research and presentation experience, through the undertaking of a research project and writing of an MSc dissertation.
CAREERS
Data science skills are some of the most highly sought after by employers both nationally and internationally. There is a rapidly increasing demand for individuals with strong proficiencies in data analysis and scientific computation. Examples of potential fields of employment (and employers) include:
- ICT (e.g. Apple, Facebook, Google, Linkedin, Microsoft, Tenable, TikTok);
- Financial services and management consulting (e.g. Accenture, AIB, Aon, Bank of Ireland, Deloitte, EY, KPMG, PWC, Zurich);
- Manufacturing and pharmaceuticals (e.g. Abbott, Eli Lilly, Glanbia, Johnson & Johnson, Regeneron);
- Research and development roles in a wide variety of applied fields, as well as strengthening applicant candidacy for application to PhD programmes
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The minimum entry requirement is a 2:2 undergraduate degree (Level 8 - ) (or equivalent) in Mathematics, Statistics, Physics, or other relevant quantitative discipline with a strong mathematical/statistical component, or equivalent qualification that is recognised by the University as meeting this requirement. The University reserves the right to shortlist and interview applicants as deemed necessary.
The MSc in Data Science and Statistical Learning requires a strong foundation in mathematics from the prior programme of study, where the expectation is that candidates excelled in their mathematical subjects; previous experience of statistical programming is an advantage but is not required.
WHAT TO INCLUDE WITH YOUR APPLICATION
- Qualification transcripts and certificates
- A copy of your birth certificate or passport
- If your qualifications have been obtained in a country where English is an official language this will suffice
- If this is not available, the following additional documents must be provided:
- English translation of your qualification(s)/transcripts AND
- English language competency certificate
- Please click here for Further Information on English Language Requirements
EU - €7,900
Non-EU - €20,100
Further information on fees and payment of fees is available from the website. All fee related queries should be directed to the Student Fees Office (Phone: +353 61 213 007 or email student.fees.office@ul.ie.)
CAREERS
Data science skills are some of the most highly sought after by employers both nationally and internationally. There is a rapidly increasing demand for individuals with strong proficiencies in data analysis and scientific computation. Examples of potential fields of employment (and employers) include:
- ICT (e.g. Apple, Facebook, Google, Linkedin, Microsoft, Tenable, TikTok);
- Financial services and management consulting (e.g. Accenture, AIB, Aon, Bank of Ireland, Deloitte, EY, KPMG, PWC, Zurich);
- Manufacturing and pharmaceuticals (e.g. Abbott, Eli Lilly, Glanbia, Johnson & Johnson, Regeneron);
- Research and development roles in a wide variety of applied fields, as well as strengthening applicant candidacy for application to PhD programmes
MSC DATA SCIENCE AND STATISTICAL LEARNING - GRADUATE PROFILE
Name: Stephen McKermitt
Course: MSc Data Science & Statistical Learning, 2023
From: Galway, Ireland
Why did you choose UL?
The last two years of my bachelor's degree were remote and I knew I wanted to continue my studies in person once the pandemic had died down. I noticed there was a real buzz around data science and artificial intelligence online which piqued my interest. After delving a bit deeper I discovered that I really enjoyed these topics and decided I would pursue them in further education. I had always wanted to attend the 51±¾É«. I would often come down to visit my friends and thought the campus and city were fantastic. I did some research and noticed that UL were running a new MSc course in data science and statistical learning.
What did you like best about your time at UL (and 51±¾É«)?
I had the pleasure of studying along side some really great people from all around the world. I really enjoyed getting to know my coursemates. All of the lecturers that I interacted with were very down-to-earth and would always be willing to lend a helping hand. I also really appreciated how well kept and modern the campus was. I quite liked the designated masters student area of the library, it was an excellent environment to get some work done.
What have you been doing since you graduated?
I started a job at ASML in the Netherlands about a month after I finished my thesis. I have been working as a technical support engineer. I spend a lot of time analysing data from ASML’s systems to try diagnose issues and brainstorm solutions. The job is a nice mix of the things I learned in my physics bachelors degree and my data science masters degree.
In what way did your course prepare you for your career?
The MSc really helped refine my problem solving skills. It also helped me gain a much greater knowledge of programming and data analysis tools. It taught me how to gain an understanding of a topic quickly.
Any advice for people thinking about coming to UL and doing this programme?
Go to as many lectures as you can, the lecturers are there to help! Get to know your coursemates, learning is more fun when it’s in groups. Have fun!