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Data Science and Statistical Learning - MSc

Course Details

Course Code: MSDSSLTFAD

Available: Full- Time

Duration: 1 Year

Award: Masters (MSc)

Qualification: Level 9 MSc Qualification

Faculty: Science and Engineering

Course Type: Taught

Fees: For Information on Fees, see section below.

Contact(s):

Name:
Dr. James A Sweeney
Email:
james.a.sweeney@ul.ie
Tel:
+353 (0) 61 202609

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

 

Autumn Semester Spring Semester Summer Semester
  • Statistical Inference for Data Science
  • Statistical Learning
  • Research Project Students will specialise their dissertation studies in one of the three sub-disciplines: Mathematics and Statistics, Electronic and Computer Engineering, or Computer Science and Information Systems

 

  • Fundamentals of Statistical Modelling
  • Quantitative Research Methods for Science, Engineering and Technology
  • Scientific Computation
  • Networks and Complex Systems
  • Database Systems in Practice
  • Applied Big Data and Visualisation
  • Text Analytics and Natural Language Processing
  • Artificial Intelligence and Machine Learning

The minimum entry requirement is a 2:2 undergraduate degree (Level 8 - National Qualifications Authority of Ireland) (or equivalent) in Mathematics, Statistics, Computer Science, or other relevant quantitative discipline, 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. 

WHAT TO INCLUDE WITH YOUR APPLICATION

  • Qualification transcripts and certificates
  • English language qualification if English is not your first language
  • Certified English translations of your transcripts/certificates where the originals are in a language other than English.
  • A copy of your birth certificate or passport.

English Language Requirements

Applicants whose first language is not English must provide evidence of either prior successful completion of a degree qualification taught through the medium of English or meet one of the criteria below (no longer than two years prior to application):

Acceptable English Language qualifications include the following:

  • Matriculation examinations from European countries where English is presented as a subject and an acceptable level is achieved
  • Irish Leaving Certificate English –Ordinary Level Grade D or above
  • TOEFL – 580 (paper based) or 90 (internet based)
  • IELTS – Minimum score of 6.5 with no less than 6 in any one component.
  • English Test for English and Academic Purposes (ETAPP) – Grade C1
  • GCE ‘O’ level English Language/GCSE English Language – Grade C or above
  • University of Cambridge ESOL –Certificate of Proficiency in English - Grade C / Certificate in Advanced English - Grade A
  • GCE Examination Boards – Oxford Delegacy of Local Examinations – Grade C / Cambridge Local Examinations Syndicate – School Certificate Pass 1-6 / University of London Entrance and School Examinations Council – School Certificate Pass 1-6

Results in examinations other than those listed above may also be accepted as meeting our English language requirements. Contact the International Education Division for advice.

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For information on funding and scholarships please click here.

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