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Data Science & Analytics

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.

Why choose this course?
The MSc in Data Science and Analytics is a significant collaboration between the Departments of Computer Science and 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. Check out our blog to find out what our graduates have to say about the course at: http://csblog.ucc.ie

Entry requirements

Candidates must have:
1.obtained either a honours level 8 primary degree (minimum 2H1 honours or equivalent) in computer science or mathematical sciences or
2.an honours level 8 primary degree (minimum 2H1 honours 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 2H1 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 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.

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.

If you are applying with Qualifications obtained outside Ireland and you wish to verify if you meet the minimum academic and English language requirements for this programme please click here to view the grades comparison table by country and for details of recognised English language tests.

Non-EU Candidates

Non-EU candidates are expected to have educational qualifications of a standard equivalent to Irish university primary degree level. In addition, where such candidates are non-native speakers of the English language they must satisfy the university of their competency in the English language. To verify if you meet the minimum academic requirements for this programme please visit our qualification comparison pages.

For more detailed entry requirement information please refer to the International website .

Duration

1 year Full Time

Careers or further progression

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 Computer Science graduates in 2016-17 include:

Accenture, Aer Lingus, Amazon, Apple, Bank of America Merrill Lynch, Bank of Ireland, BT, Cisco, CiTi-Technology, Cloudreach, Dell, Digital Turbine Asia Pacific, EMC, Enterprise Ireland, Ericsson, First Derivatives, Guidewire, IBM, Intel, Open Text, Paddy Power, Pilz, PWC, SAP Galway Transverse Technologies, Trend Micro, Uniwink, Version 1 (Software).

Starting Salaries

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 €35,000-70,000 depending on industry and experience.

Further enquiries

Prof. Barry O'Sullivan
Email:b.osullivan@cs.ucc.ie
Tel:021 420 5951

Dr Eric Wolsztynski
Email:eric.w@ucc.ie
Tel:+353 (0)21 420 5823

Subjects taught

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 coordinator
CS6405 Data Mining (5 credits) - Dr Marc Van Dongen, Semester 2
ST6030 Foundations of Statistical Data Analytics (10 credits) - Dr Michael Cronin, Semester 1
ST6033 Generalised Linear Modelling Techniques (5 credits) - Dr Michael Cronin, Semester 2

Database Modules

Students who have adequate database experience take:
CS6408 Database Technology (5 credits) - Mr Humphrey Sorensen, Semester 1
CS6409 Information Storage and Retrieval (5 credits) - Mr Humphrey Sorensen, Semester 2

Students who have not studied databases take:
CS6503 Introduction to Relational Databases (5 credits) - Dr Kieran Herley, Semester 1
CS6505 Database Design and Administration (5 credits) - Mr Humphrey Sorensen, Semester 2

ELECTIVE MODULES (30 credits) - All selections are subject to approval of the programme coordinator
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
CS6323 Analysis of Networks and Complex Systems (5 credits) - Professor Gregory Provan, Semester 2
CS6509 Internet Computing for Data Science (5 credits) - Dr David Stynes, Semester 1
ST6032 Stochastic Modelling Techniques (5 credits) - Professor Finbarr O'Sullivan, Semester 1
ST6034 Multivariate Methods for Data Analysis (10 credits) - Dr Michael Cronin, Semester 2
ST6035 Operations Research (5 credits) - Professor Finbarr O'Sullivan, Semester 1
ST6036 Stochastic Decision Science (5 credits) - Professor Finbarr O'Sullivan, Semester 2

Programming Modules
Students who have adequate programming experience take:
CS6406 Large-Scale Application Development and Integration I (5 credits) - Prof. Gregory Provan, Semester 1
CS6407 Large-Scale Application Development and Integration II (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

PART 2 (30 credits)
Students select one of the following modules, which is undertaken after Semester 2 examination results are known:
CS6500 Dissertation in Data Analytics (30 credits) - Professor Gregory Provan, Semester 3
ST6090 Dissertation in Data Analytics (30 credits) - Dr Michael Cronin, Semester 3

Comment

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.

Assessment method

Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2016 Book and for each module in the Book of Modules 2016/2017.

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.

Application date

Closing dates

Closing Dates for Application

Applications for 2018 start dates will open on November 1st 2017.

EU Applicants: UCC operates a rounds closing date system for the majority of postgraduate taught programmes (detailed below).

Some programmes have a specific closing date. Applicants are advised to consult with the postgraduate prospectus for programmes with a specific closing date.

The UCC rounds EU application system closing dates for Postgraduate Taught courses are detailed below. However, we would advise applicants to apply as soon as possible.

Deadline for receipt of Applications: Offers will be made:
For all completed applications received by January 15th 2018 Offers will be made by January 29th 2018

For all completed applications received by March 1st 2018 Offers will be made by March 15th 2018

For all completed applications received by May 1st 2018
Offers will be made by May 15th 2018

For all completed applications received by July 2nd 2018
Offers will be made by July 16th 2018

Late applications may be accepted on a first-come, first-served basis for any courses that have remaining capacity for places.

While there is no official closing date for Research courses applicants are advised to submit their application at least two months ahead of their proposed start date. There are four official Research start dates – September/October, January, April and July.

Non-EU Applicants:

Please visit the following page for further information for Non EU applicants http://www.ucc.ie/en/international/studyatucc/postgraduateprogrammes/tau...

Enrolment and start dates

Start Date: 10th September 2018

Remember to mention gradireland when contacting institutions!