Data Science and Analytics MSc

Fact File

Course Code: CKR49 Full-time, CKR50 Part-time

Course Title: Data Science and Analytics

College: Science, Engineering and Food Science

Data Science and Analytics

Duration: 1 year Full Time; 2 years Part Time

Teaching Mode: Full-time, Part-Time

The part-time option will be taught during weekday working hours over 2 years.

Qualifications: MSc

NFQ Level: Level 9

Costs: 2015/2016 Irish/EU €7,000 Fees for 2016/17 TBC

2016 Entry Requirements: See detailed entry requirements

Closing Date: See detailed application procedure section below

Next Intake: 12th September 2016


The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. The combination of sophisticated computing and statistics modules will develop skills in database management, programming, summarisation, modelling and interpretation of data. The programme provides graduates with an opportunity, through development of a research project, to investigate the more applied elements of the disciplines.

For further information see our brochure at:

Course Details

Programme Structure: 

Students must attain 90 credits through a combination of: 

  • Core Modules (30 credits)
  • Elective Modules (30 credits)
  • Dissertation (30 credits)

Students take 90 credits as follows:

Part 1 (60 credits)

Core Modules (30 credits) - All selections are subject to approval of the Programme Co-ordinator

CS6405 Data Mining (5 credits) - Dr. Marc Van Dongen
ST6030 Foundations of Statistical Data Analytics (10 credits)
ST6033 Generalised Linear Modelling Techniques (5 credits)

Database Modules
Students who have adequate database experience take: 

CS6408 Database Technology (5 credits) - Mr. Humphrey Sorensen
CS6409 Information Storage and Retrieval (5 credits) - Mr. Humphrey Sorensen 

Students who have not studied databases take: 

CS6503 Introduction to Relational Databases (5 credits)
CS6505 Database Design and Administration (5 credits)

Elective Modules (30 credits) - All selections are subject to approval of the Programme Co-ordinator
Students must take at least 10 credits of CS (Computer Science) modules and at least 10 credits of ST (Statistics) modules from those listed below:

CS6322 Optimisation (5 credits) - Dr. Steve Prestwich
CS6323 Analysis of Networks and Complex Systems (5 credits) - Prof. Gregory Provan
CS6509 Internet Computing for Data Science (5 credits)
ST6032 Stochastic Modelling Techniques (5 credits)
ST6034 Multivariate Methods for Data Analysis (10 credits)
ST6035 Operations Research (5 credits)
ST6036 Stochastic Decision Science (5 credits)

Programming Modules
Students who have adequate programming experience take: 

CS6406 Large-Scale Application Development and Integration l (5 credits) - Professor Gregory Provan
CS4607 Large-Scale Application Development and Integration ll (5 credits) - Professor Gregory Provan

Students who have not studied programming take: 

CS6506 Programming in Python (5 credits)
CS6507 Programme in Python with Data Science and Applications (5 credits) - Dr. Kieran Herley

Part 2 (30 credits)
Students select one of the following modules:

CS6500 Dissertation in Data Analytics (30 credits)
ST6090 Dissertation in Data Analytics (30 credits)


Detailed Entry Requirements

Candidates must have:

  1. obtained either a second class honours level 8 primary degree (or equivalent) in computer science or mathematical sciences or
  2. a second class honours level 8 primary degree (or equivalent) with a strong numerate content (e.g. engineering, finance, physics, biosciences or economics). In such cases the programme team must be satisfied that the numerate content is sufficient for entry to the programme and that applicants have an aggregate grade of a 2H2 in appropriate modules.

Applicants who do not meet the above standard entry requirements will also be considered if they have an undergraduate degree (at Level 7 or > Level 8) and a minimum of 5 years verifiable relevant industrial experience.

Applicants who do not have a primary degree will only be considered with a minimum of 10 years verifiable relevant industrial experience.

Shortlisted applicants who do not meet the standard entry requirements will be invited for interview.

Candidates, for whom English is not their primary language, should possess an IELTS score of 6.5, with no individual section lower than 6.0.

Candidates from Grandes Écoles Colleges are also eligible to apply if they are studying a cognate discipline in an ENSEA or EFREI Graduate School and are eligible to enter the final year (M2) of their programme

Application Procedure

Application for this programme is on-line at Places on this programme are offered in rounds. The closing dates for each round can be found here. For full details of the application procedure click How to Apply.

All required documentation must be either uploaded to your online application, or sent in hard copy to The Postgraduate Applications Centre, 1, Courthouse Square, Galway, immediately after an application is made.

Course Practicalities

A typical 5 credit module:

•             2 lecture hours per week

•             1–2 hours of practicals per week

•             Outside these regular hours students are required to study independently by reading and by working in the laboratories and on exercises.


Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2015 Book and for each module in the Book of Modules 2015/2016.

Postgraduate Diploma in Data Science and Analytics
Students who pass each of the taught modules may opt to exit the programme and be conferred with a Postgraduate Diploma in Data Science and Analytics.



Further Contact Information

Professor Gregory Provan, Department of Computer Science


T: +353 (0)21 4905928


Dr Michael Cronin, Department of Statistics


T: +353 (0)21 420 5825

Contact us

E: Gregory Provan

P: 021 420 5928
W: Website

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