UCC Undergraduate courses

Data Science and Analytics

About This Course

Fact File

  • Title

    Data Science and Analytics

  • Code

    CK411

  • College

    Science, Engineering and Food Science

  • Duration

    4 years

  • Teaching Mode

    Full-time

  • Qualifications

    BSc (Hons)

  • Fees

    Student Contribution + Capitation: €3,165 See Fees and Costs for full details.

  • Entry Requirements

    1 x H3, 1 x H5, 4 x O6/H7; H3 in Maths. See Requirements for full details.

  • CAO Points

    2018: 455

Course Outline

Data Science & Analytics focuses on new ways to capture and understand data from the world around us.  It helps us make better decisions for people, communities and industry. The BSc in Data Science & Analytics at UCC provides an education in data storage, manipulation and interpretation using mathematical sciences and computational methods which assists us solve complex real-world problems.

In the first and second year, you will study the mathematical and computational foundations of data science and analytics.

During the third year, you begin applying the fundamentals of data science and analytics to real life problems and data. In Spring of third year, you undertake a six-month work placement (paid in most cases) providing an opportunity to apply the knowledge they have learnt in a work-place environment.

In the fourth year, you choose specialised modules and undertake an independent project, which enables them to investigate more applied elements of the discipline.

Firms specialising in analytics, financial services and consulting, and governmental agencies to name but a few are currently seeking graduates with data analytics skills to fill a range of positions.

Year 1 Modules

CORE 

  • CS1106 Introduction to Relational Databases;
  • CS1112 / CS1113 Foundations of Computer Science I / II;
  • CS1117 Introduction to Programming;
  • AM1054 Mathematical Software;
  • MA1058 Introduction to Linear Algebra;
  • MA1059 Calculus;
  • ST1050 Statistical Programming in R;
  • ST1051 Introduction to Probability and Statistics.

ELECTIVES:

  • AM1053 Introduction to Mathematical Modelling OR ST1401 Introduction to Operations Research

 

Year 2

CORE:

  • CS2208 / CS2209 Information Storage and Management I / II;
  • CS2513 Intermediate Programming;
  • CS2514 Introduction to Java;
  • CS2515 / CS2516 Algorithms and Data Structures I / II;
  • MA2055 Linear Algebra;
  • MA2071 Multivariable Calculus;
  • ST2053 Introduction to Regression Analysis;
  • ST2054 Probability and Mathematical Statistics.

ELECTIVES:

  • AM2052 Mathematical Modelling OR ST2402 Modelling and Systems for Decision Making.


Year 3

CORE:

  • CS3220 Work Placement DSA;
  • CS3306 Workplace Technology and Skills;
  • CS3204 Cloud Infrastructure and Services;
  • CS3318 Advanced Programming with Java;
  • CS3509 Theory of Computation;
  • CS3205 Data Visualization for Analytics Applications;
  • ST3053 Stochastic Modelling I;
  • ST3061 Statistical Theory of Estimation;
  • ST3070 Statistical Theory of Hypothesis Testing;
  • ST3069 Generalised Linear Models.


Year 4

CORE:

  • CS4701 Analytics Project for Computer Science OR ST4092 Data Analytics Project;
  • CS4704 Algorithms and Data Structures for Analytics;
  • CS4705 Computational Machine Learning;
  • ST4060 / ST4061 Computer Intensive Statistical Analytics I / II;
  • ST4069 Multivariate Methods for Data Analysis.

ELECTIVES:

  • AM4006 Mathematical Modelling of Biological Systems with Differential Equations (online);
  • AM4010 Topics in Applied Mathematical Modelling (online);
  • AM2061 Computer Modelling and Numerical Techniques;
  • AM3064 Computational Techniques;
  • ST3054 Survival Analysis;
  • ST4064 Time Series;
  • ST4090 Current Topics in Statistics I;
  • CS4150 Principles of Compilation;
  • CS4405 Multimedia Compression and Delivery;
  • CS4407 Algorithm Analysis;
  • CS4413 Future and Emerging Technologies;
  • CS4614 Introductory Network Security;
  • CS4615 Computer Systems Security;
  • CS4616 Distributed Algorithms;
  • CS4620 Functional Programming I;
  • CS4626 Constraint Programming and Optimisation;
  • CS4710 Programming Paradigms for Big Data.

 

 

Course Practicalities

Expected lecture/lab hours: This is a full-time course expecting a full-time commitment. The annual 60-credits workload typically equates to 12 hours of lectures per week and a comparable amount for laboratory work and tutorials.

Expected reading/practical hours: The course also demands a significant amount of additional time for study, reading, completion of project and assignment work.

Why Choose This Course

The BSc DSA at UCC is one of two such programmes being offered in Ireland and amongst a dozen offered worldwide. 

This programme is will suit you if have an aptitude for mathematics, logic and computational thinking, an enquiring mind and a willingness to adapt.

The degree is a jointly offered by the Departments of Computer Science and Statistics and is closely associated with Insight – the Centre for Data Analytics, which is a national SFI centre. UCC has expertise in both statistics and computer science that is second to none.

Graduates of the UCC BSc in Data Science and Analytics have vast opportunities in a wide variety of industries as there is a high global demand for graduates with data science expertise. Almost all sectors of the economy and community need to understand the enormous data sets available.

Placement or Study Abroad Information

The BSc Data Science & Analytics aims to ensure that you are work-ready. Work placement is a core module undertaken from Spring until August in Year 3.

To find a placement organisation, you will work with the Careers Service; they will help you with interviews and keep in contact with you during placement. Working in a company setting provides you with additional skills that cannot be taught through lectures or in the laboratory. During placement, you will work as part of a team to solve real problems. Your placement is jointly monitored by a UCC staff member and an employee of the company.

Skills and Careers Information

Job prospects are buoyant:

Data Scientist is the most highly recruited degree (InfoWorld, 2017)

  • Top in salary

o   Top in job satisfaction

 

  • Demand will only increase

 

IBM Predicts Demand for Data Scientists Will Soar 28% By 2020 (Forbes, May 2017)

Practically all sectors of the economy employ Data Scientists.  The following list provides some insight into sectors / companies that use such skills.

Banking (for example AIB, BoI, Central Bank, Citi...)
Energy (for example Bord Gas, Electric Ireland…)
Financial Services (for example Elavon, Pramerica…)
Food & Agriculture (for example Kerry, Glanbia…)
Gaming (for example Paddy Power, Xanadu, Betbright…)
Government (for example CSO, Revenue, HSE…)
Health (for example HSE, HIQA, Optum…)
Insurance (for example Allianz, Aviva, Aon…)
Management Consultancy (for example EY, PWC, FTI Consulting, Deloitte, Accenture, Clarion, KPMG…)
Marketing, Media & Communication (for example Core Media, Vodafone, Eir, 3…)
Pharmaceutical (for example Abbott, Novartis, Regeneron, Johnson and Johnson, Pfizer…)
Research (for example ESRI, Universities, Insight…)
Retail (for example Dunnes Stores, Tesco, Super Valu, Amazon, Wayfair…)
Software (for example SAS, SPSS…)
Sport (for example Munster Rugby, GAA, RTE, Sky Sports...)
Technology (for example IBM, EMC, HP, Apple, Microsoft, Google, Dell, Facebook, Intel, Version 1…)

Requirements

Leaving Certificate entry requirements

At Least six subjects must be presented. Minimum grade H3 in one subject, minimum grade H5 in one subject and minimum grade O6/H7 in four other subjects.  English and Irish are requirements for all programmes unless the applicant is exempt from Irish. 
Applicants will need to meet the following minimum entry requirements:

English

Irish

Maths

O6/H7

O6/H7

H3

Non-EU Candidates

Non-EU candidates are expected to have educational qualifications of a standard equivalent to the Irish Leaving Certificate. 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 and language requirements for this programme please visit our qualification comparison pages.

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

Mature Students Requirements

Please refer to the mature student entry requirements for details. 

Fees and Costs

The State will pay the tuition fees for students who satisfy the Free Fees Criteria. In 2017/18 the Student Contribution Charge was €3,000 and the Capitation Fee was €165. Full-time EU/EEA/Swiss State undergraduate students may be exempt from paying tuition fees.

Non-EU Fees

The 2017/2018 Undergraduate Fees Schedule is available here.

How Do I Apply

Non-EU Applications

Applicants who are interested in applying for the programme can apply online.

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

 

**All Applicants please note: modules listed in the course outline above are indicative of the current set of modules for this course, but these are subject to change from year to year. Please check the college calendar for the full academic content of any given course for the current year. 

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. 

For queries regarding course content or timetables please contact

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