About This Course
Data Science & Analytics
1 year full-time
See Fees and Costs for full details.
See Requirements for full details.
Open for EU applications, check rounds closing dates under How to Apply
Non-EU Closing Date
Closed now for applications. Check out www.ucc.ie/ictpgoptions
12 September 2022
Our 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 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)
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)
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)
See the University Calendar (MSc Data Science & Analytics) for further course and module content.
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.
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 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
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.
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; see the Brightwater Salary Survey 2020 for an overview of salaries across relevant industries.
Candidates must have:
- Second Class Honours Grade I in a primary honours degree (NFQ, Level 8) in computer science or mathematical sciences or
- 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.
English Language Requirements
Applicants that are non-native speakers of the English language must meet the university-approved English language requirements. Please visit our PG English Language Requirements page for more information.
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.
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.
Fees and Costs
The EU fee for this course is €7,130.
The Non-EU fee for this course is €18,500.
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
International Students can pay in two equal instalments once they have paid the appropriate deposit. The initial payment is due on registration and the balance usually by the end of January.
How can I pay?
You can pay by Credit/Debit card online or by credit transfer.
If you have any questions on fee payment please email our Fees Office at firstname.lastname@example.org.
How Do I Apply
1. Apply online
Once you have chosen your course you can apply online via the online application portal. Applicants will need to apply before the course closing date. The majority of our courses have a non-refundable €50 application fee.
2. 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.
3. 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.
Any questions? 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 Closed now for applications. Check out www.ucc.ie/ictpgoptionsApply Now