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UCC Postgraduate courses

Data Science & Analytics

Course Fact File
Duration1 Year Full-time
Teaching ModeFull-time
NFQ LevelLevel 9
Closing DateThis course is now closed for new applications.
Non-EU Closing DateThis course is now closed for new applications.
Start Date9 September 2024

Course Outline

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

Students must attain 90 credits through a combination of core modules (30 credits), elective modules (30 credits) and a dissertation (30 credits). 

PART I (60 credits)

Core Modules (30 credits)

  • CS6405 Datamining (5 credits) 
  • CS6421 Deep Learning (5 credits) 
  • 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) 

Students who have not studied databases take:

  • CS6503 Introduction to Relational Databases (5 credits) 

Elective Modules (30 credits) 

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) 
  • CS6409 Information Storage and Retrieval (5 credits) 
  • CS6420 Topics in Artificial Intelligence (5 credits) Semester 1
  • CS6426  Data Visualization for Analytics Applications (5 credits) 
  • ST6034 Multivariate Methods for Data Analysis (10 credits)
  • ST6035 Operations Research (5 credits)
  • ST6036 Stochastic Decision Science (5 credits)
  • ST6040 Machine Learning and Statistical Analytics I (5 credits)
  • ST6041 Machine Learning and Statistical Analytics II (5 credits)

Programming Modules

Students who have adequate programming experience take:

  • CS6422 Complex Systems Development (5 credits) 
  • CS6423 Scalable Computing for Data Analytics (5 credits) 

Students who have not studied programming take:

  • CS6506 Programming in Python (5 credits) 
  • CS6507 Programming in Python with Data Science Applications (5 credits) 

All selections are subject to the approval of the programme coordinator.

PART II (30 credits)

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

Postgraduate Diploma in Data Science & 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 & Analytics.

Academic Programme Catalogue

See the Academic Programme Catalogue where you can search for the complete and up-to-date content for this course. Note that the modules for all courses are subject to change from year to year. For complete descriptions of individual modules, see the Book of Modules.

Course Practicalities

A typical 5-credit module entails:

  • 2 lecture hours per week;
  • 1–2 hours of practicals per week;
  • and outside of these regular hours, students are required to study independently by reading and by working in the laboratories and on exercises.

Why Choose This Course

Graduates of this degree program will fulfil an increasing demand for technical staff with these skills across the IT sector...

Donagh Buckley, Research Director, EMC Ireland

Find Out More

This programme entails a significant collaboration between the School of Computer Science and Information Technology, and the Department of Statistics. It is designed to provide graduates with the skills and knowledge required to help companies and public bodies deal with ever-increasing and complex data.  We emphasise the application of Computer Science and Statistics methodologies helping transform data into useful information that can support decision making. 

Skills and Careers Information

Our MSc programme aims to prepare students to manage, analyse and interpret large heterogeneous data sources. Our graduates will design, compare and select appropriate data analytic techniques, using software tools for data storage/management and analysis, machine learning, as well as probabilistic and statistical methods. Such abilities are at the core of companies that constantly face the need to deal with large data sets.

Companies currently seeking graduates with data analytics skills include: firms specialising in analytics, financial services and consulting, or governmental agencies.

Companies actively recruiting our graduates:

Accenture, Aer Lingus, Agility M3, Allied Irish Banks, Altada Technology Solutions Ltd, Amazon, Apple, Bank of America Merrill Lynch, Bank of Ireland, BT, Central Statistics Office, Cisco, CiTi-Technology, Clearstream, Cloudreach, Dell EMC, Deloitte, Deutche Bank, Enterprise Ireland, Ericsson, Ernst & Young, Ervia, Facebook, First Derivatives, Google, Guidewire, Intel, IBM, Janssen, KPMG, Logitech, Microsoft, Open Text, Paddy Power, Pfizer, Pilz, PWC, SAP Galway, Screendragon, Transverse Technologies, Trend Micro, Tyco, Uniwink, Verizon Connect,  Snipp Interactive, Version 1 (Software), Virgin One, VMware and more.



Candidates must have:

  1. Second Class Honours Grade I in a primary honours degree (NFQ, Level 8) in computer science or mathematical sciences or
  2. Second Class Honours Grade I in a primary honours degree (NFQ, Level 8) 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 Second Class Honours Grade II in appropriate modules.

Applicants who do not meet the above standard entry requirements will also be considered under Recognition of Prior Learning (RPL) if they have an undergraduate degree (NFQ, Level 8) and a minimum of 5 years of verifiable relevant industrial experience.

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

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.

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

Non EU applicants, who are required to present an English language proficiency test, must present the certificate on submission of initial application in order for the application to be considered. 

For Applicants with Qualifications Completed Outside of Ireland

Applicants must meet the required entry academic grade, equivalent to Irish requirements. For more information see our Qualification Comparison page.

International/Non-EU Applicants

For full details of the non-EU application procedure visit our how to apply pages for international students.

  • In UCC, we use the term programme and course interchangeably to describe what a person has registered to study in UCC and its constituent colleges, schools, and departments.
  • Note that not all courses are open to international/non-EU applicants, please check the fact file above. For more information contact the International Office.
English Language Requirements

Applicants who are non-native speakers of the English language must meet the university-approved English language requirements. Visit our PG English Language Requirements page for more information.

Fees and Costs

Postgraduate EU and International Fees 2024/2025

See our Postgraduate EU and Non-EU (International) Fee Schedule for the latest information.


If your course requires a deposit, that figure will be deducted from your second-semester fee payment in January.

Fee payment 

Fees are payable in two equal instalments. First payment is at registration and the balance usually by the end of January.

How can I pay? 

See different options on our How Do I Pay My Fees? page.

Any questions? See the 'Contact Us' section on the Fees Office page.

How To Apply

1. Check dates

Check the opening and closing dates for the application process in the fact file boxes at the top of the page.

2. Gather documents

Scanned copies of supporting documents have to be uploaded to the UCC online application portal and include:

  • Original qualification documents listed on your application including transcripts of results from institutions other than UCC.
  • Any supplementary items requested for your course if required.

3. Apply online

Apply online via the UCC online application portal. Note the majority of our courses have a non-refundable €50 application fee.

Any questions? Use our web enquiry form to contact us.

International Non-EU Applicants

Entry to this programme is highly competitive, and therefore applicants who present all required documentation at the time of application will be prioritised for processing.


Please note that successful EU applicants will be required to pay a non-refundable deposit of €500 on acceptance of their place.

The closing date for non-EU applications is This course is now closed for new applications.

Apply Now

For queries regarding course content or timetables please contact