About This Course
Data Science and Analytics
1 year Full Time
EU Fees 2021
See Fees and Costs for full details.
Non-EU Fees 2021
See Requirements for full details.
Open for EU applications, check rounds closing dates under How to Apply
Non-EU Closing Date
Temporarily closed for application. May reopen if space available.
13 September 2021
The MSc in Data Science & Analytics, jointly offered by the School of Computer Science and Information Technology 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 your skills in database management, programming, summarisation, modelling, data visualisation, 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.
Students must attain 90 credits through a combination of core modules (30 credits), elective modules (30 credits) and a dissertation (30 credits).
PART 1 (60 credits)
Core Modules (30 credits)
- CS6405 Datamining (5 credits) – Dr Alejandro Arbelaez, Semester 2
- CS6421 Deep Learning (5 credits) – Prof Gregory Provan, Semester 2
- ST6030 Foundations of Statistical Data Analytics (10 credits) - Dr Michael Cronin & Dr Supratik Roy, Semester 1
- ST6033 Generalised Linear Modelling Techniques (5 credits) - Dr Michael Cronin, Semester 2
Students who have adequate database experience take:
- CS6408 Database Technology (5 credits) - Dr Colin McCormack, Semester 1
Students who have not studied databases take:
- CS6503 Introduction to Relational Databases (5 credits) - Dr Kieran Herley, Semester 1
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) - Dr Steve Prestwich, Semester 1
- CS6409 Information Storage and Retrieval (5 credits) - Dr Alejandro Arbelaez, Semester 2
- CS6420 Topics in Artificial Intelligence (5 credits) – Prof Barry O’Sullivan, Semester 1
- ST6034 Multivariate Methods for Data Analysis (10 credits) - Dr Michael Cronin & Dr Supratik Roy, Semester 2
- ST6035 Operations Research (5 credits) – Dr Maria Teider, Semester 1
- ST6036 Stochastic Decision Science (5 credits) – Dr Kevin Hayes, Semester 2
- ST6040 Machine Learning and Statistical Analytics I (5 credits) - Dr Eric Wolsztynski, Semester 1
- ST6041 Machine Learning and Statistical Analytics II(5 credits) - Dr Eric Wolsztynski, Semester 2
Students who have adequate programming experience take:
- CS6422 Complex Systems Development (5 credits) – Prof Gregory Provan, Semester 1
- CS6423 Scalable Computing for Data Analytics (5 credits) - Prof Gregory Provan, Semester 2
Students who have not studied programming take:
- CS6506 Programming in Python (5 credits) - Dr Kieran Herley, Semester 1
- CS6507 Programming in Python with Data Science Applications (5 credits) - Dr Kieran Herley, Semester 2
All selections are subject to the approval of the programme coordinator.
PART 2 (30 credits)
A student who obtains an aggregate mark of at least 60% across the taught modules, and not less than 40% in the Dissertation in Data Science and Analytics will be eligible for the award of the MSc Data Science and Analytics.
Eligible students select one of the following modules:
- CS6500 Dissertation in Data Analytics (30 credits) - Dr Ahmed Zahran, Semester 3
- ST6090 Dissertation in Data Analytics (30 credits) - Dr Michael Cronin, Semester 3
The Book of Modules contains descriptions for all modules listed in the University Calendar. Selection of any modules is governed by the programme requirements outlined in the University Calendar for each programme.
Further details on the modules listed above can be found in our book of modules. Any modules listed above are indicative of the current set of modules for this course but are subject to change from year to year.
You can find the full academic content for the current year of any given course in our University Calendar.
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.
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.
Why Choose This Course
The MSc in Data Science and Analytics is a significant collaboration between the School of Computer Science and Information Technology, and Department of Statistics, designed to provide graduates with the skills and knowledge required to help companies and public bodies deal with ever increasing and complex data. The programme emphasises the application of Computer Science and Statistics methodologies helping transform data into useful information that can support decision making.
Skills and Careers Information
This programme aims to prepare students to manage, analyse and interpret large heterogeneous data sources. 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), VMware, and more.
There is an increasing demand for graduates that can collate, interpret, manage and store large volumes of data. Graduates can be employed as analysts, database administrators, data warehouse consultants, business intelligent consultants to name but a few. Employment agencies report typical salaries ranging from €45,000-€95,000 depending on industry and experience.
Salaries are in general higher than many other industries. The following link provides details of the Brightwater Salary Survey 2020.
Candidates must have:
- obtained either a Second Class Honours Grade I in a primary honours degree (NFQ, Level 8) in computer science or mathematical sciences or
- a 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 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.
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 interview.
English Language Requirements
Applicants that are non-native speakers of the English language must meet the university approved English language requirements available here.
For applicants with qualifications completed outside of Ireland
Applicants must meet the required entry academic grade, equivalent to Irish requirements, please find our grades comparison by country here.
For full details of the non-EU application procedure please 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.
Not all courses are open to international/non-EU applicants, please check the fact file above.
For more information please contact the International Office.
Fees and Costs
The EU fee for this course is €7,130.
The Non-EU fee for this course is €18,130.
If your course required a deposit, that figure will be deducted from your second semester fee payment in January.
EU student fee payment:
Fees for EU students are payable in two equal instalments. First payment at registration in August and the second in January.
International student fee payment:
Fees for Non-EU Students are payable in one instalment in August.
How can I pay?
By Credit/Debit card online or by credit transfer.
If you have any questions on fee payment please email our Fees Office at email@example.com .
The fee schedule for 2019/2020 is available here.
How Do I Apply
1. Choose Course
Firstly choose your course. Applicants can apply for up to two courses under one application. Details of taught courses are available on our online prospectus.
2. Apply Online
Once you have chosen your course you can apply online at the online application portal. Applicants will need to apply before the course closing date. There is a non-refundable €50 application fee for all courses apart from the Education - Professional Master of Education - (Secondary School/Post-Primary Teacher Training) which has a €100 application fee.
Applicants for the Postgraduate Diploma in Public Health Nursing must apply on the PAC website when the programme opens for applications.
3. Gather Supporting Documents
Scanned copies of the following documents will need to be uploaded to the online application portal in support of your application. Applicants may need to produce the original documents if you are accepted onto a course and register at UCC.
- Original qualification documents listed on your application including transcripts of results from institutions other than UCC
- Any supplementary items requested for your course.
Please log into the online application portal for more details.
4. Application processing timeline
Our online application portal opens for applications for most courses in early November of each year. Check specific course details.
For courses that are in the rounds system (Irish and EU applicants), please check the rounds closing dates here.
Questions on how to apply?
Please use our web enquiry form to contact us.
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 Temporarily closed for application. May reopen if space available.Apply Now