Data Science and Analytics MSc - CKR49 full time. CKR50 part time

Fact File

Course Title: Data Science and Analytics

College: Science, Engineering and Food Science

Data Science and Analytics

Duration: 1 year Full Time or 2 years Part Time

Teaching Mode: Full-time, Part-Time

Qualifications: MSc

NFQ Level: Level 9

Costs: 2014/2015 Irish/EU €5,500

Entry Requirements: See detailed entry requirements

Course Code: CKR49 full time. CKR50 part time

Closing Date: Currently open for late applications

Next Intake: 8th September 2014


This programme of the Department of Computer Science and the School of Mathematical Sciences provides an education in the key principles of the rapidly-developing area of Data Science and Analytics.  In addition to the basic computational underpinnings of this field, a sequence of courses in probability and statistics will develop skills in analysis, summarisation and modelling of data.

The programme also allows graduates an opportunity, through development of a research portfolio, to investigate the more applied elements of the discipline. At all times the programme stresses the importance of data science, statistics and probability theory as key tools in the analysis of large-scale heterogeneous data.

Companies are currently seeking graduates with data analytics skills to fill a range of positions including firms specialising in analytics, financial services and consulting, and governmental agencies.

Below please find link to brochure for further information see our brochure at

Course Details

Students must attain ninety credits through a combination of core modules (30 credits) and elective modules (30 credits) in periods 1 & 2 and a dissertation (30 credits) during the summer period. 


  • CS6401 (Advanced Information Storage and Retrieval [10 credits] * or CS6503 (Introduction to Relational Databases) [5 credits] plus CS6505 (Database Design and Administration)
  • ST6030 (Foundations of Statistical Data Analytics) [10 credits]
  • ST6033 (Generalised Linear Modelling Techniques) [5 credits]
  • CS6401 (Advanced Information Storage and Retrieval)  or CS6405 Data Mining [5 credits]


  • CS6322 (Optimisation) [5 credits]
  • CS6506 (Programming in Python)  or CS6404 (Large-Scale Application Development and Integration) [5 credits]   *
  • CS6509 (Internet Computing) [5 credits]
  • ST6031 (Operations Research and Stochastic Decision Science) [5 credits]
  • ST6032 (Stochastic Modelling Techniques) [5 credits]
  • CS6507 (Programming  in Python with Data Science Applications) or CS6404 (Large-Scale Application Development and Integration) [5 credits]  *
  • CS6323 (Analysis of Networks and Complex Systems) [5 credits]
  • ST6031 (Operations Research and Stochastic Decision Science) [5 credits]
  • ST6034 (Multivariate Methods for Data Analysis) [10 credits]


CS6500 (Dissertation in Data Analytics) or ST6090 (Dissertation in Data Analytic) [30 credits]

* - Choice subject to approval of programme coordinator.

Module descriptions can be found at

Based on this programme, candidates will gain experience in storing, processing and analysing "big data", thereby translating the data to expose the content contained in the data. The programme provides the following core expertise:

  • database (CS6401 or CS6503 and CS6505): provides data storage expertise
  • analytics (ST6030, ST6033, CS6405): provide core analytics expertise

There are several elective sequences that provide the following expertise:

  • programming (CS6404 or CS6506 and CS6507)
  • advanced analytics (ST6031, ST6032, ST6034)
  • IT (CS6322, CS6323, CS6509)

Finally, hands-on experience will be obtained through the dissertation, focusing on analytics (ST6090) or computational methods (CS6500).

Detailed Entry Requirements

  1. obtained either a second class honours level 8 primary degree in computer science or mathematical sciences or
  2. a second class honours level 8 primary degree 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.

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.


The MSc in Data Science & Analytics will be examined through a combination of:

  • Mid-term exams
  • End-of-term exams
  • Assignments


Further Contact Information

Dr Michael Cronin, Department of Statistics


T: +353 (0)21 420 5825

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