UCC Undergraduate courses

Data Science and Analytics (Available from 2018)

About This Course

Fact File

  • Title

    Data Science and Analytics (Available from 2018)

  • 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

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

Course Outline

Data Science & Analytics focuses on new ways to capture and understand data from the world around us, to 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 to solve complex real world problems.

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

In third year, students begin applying the fundamentals of data science and analytics to real life problems and data. That year is then completed with a six-month work placement (paid in most cases) providing an opportunity to apply the skills learnt in a work-place environment.

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

Companies are currently seeking graduates with data analytics skills to fill a range of positions including firms specialising in analytics, financial services and consulting, and governmental agencies.

Year 1 Modules

Core

CS1106 Introduction to Relational Databases (5 credits)

CS1112 Foundations of Computer Science I (5 credits)

CS1113 Foundations of Computer Science II (5 credits)

CS1117 Introduction to Programming (15 credits)

AM1054 Mathematical Software (5 credits)

MA1058 Introduction to Linear Algebra (5 credits)

MA1059 Calculus (5 credits)

ST1050 Statistical Programming in R (5 credits)

ST1051 Introduction to Probability and Statistics (5 credits)


Electives
: 5 credits

AM1053 Introduction to Mathematical Modelling (5 credits) OR

ST1401 Introduction to Operations Research (5 credits)

Year 2 Modules

Core

Information Storage and Management I; Information Storage and Management II; Intermediate Programming; Introduction to Java; Algorithms and Data Structures I; Algorithms and Data Structures II; Linear Algebra; Multivariable Calculus; Introduction to Regression Analysis;Probability and Mathematical Statistics 

Electives

Mathematical Modelling; Modelling and Systems for Decision Making

 
Year 3 Modules

Core

Work Placement DSA; Workplace Technology and Skills; Cloud Infrastructure and Services; Advanced Programming with Java; Theory of Computation; Data Visualization for Analytics Applications; Stochastic Modelling I; Statistical Theory of Estimation; Statistical Theory of Hypothesis Testing; Generalised Linear Models 

 
Year 4 Modules

Core

Analytics Project for Computer Science OR Data Analytics Project; Algorithms and Data Structures for Analytics; Computational Machine Learning; Computer Intensive Statistical Analytics I; Computer Intensive Statistical Analytics II; Multivariate Methods for Data Analysis 

 
Electives

Mathematical Modelling of Biological Systems with Differential Equations; Topics in Applied Mathematical Modelling; Partial Differential Equations with Applications I; Computational Techniques; Survival Analysis; Time Series; Current Topics in Statistics I; Principles of Compilation; Multimedia Compression and Delivery; Algorithm Analysis; Future and Emerging Technologies; Introductory Network Security; Computer Systems Security; Distributed Algorithms; Functional Programming I; Constraint Programming and Optimisation; 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

This programme is suited to students who have an aptitude in 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, each Department contributing half of the modules. 

Both Departments have many academics expert in teaching and research in the area.  Insight – Centre for Data Analytics is located in the Department of Computer Science and is a national centre for data analytics. 

The job prospects for graduates of the UCC BSc in Data Science and Analytics are significant, 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 our graduates are work-ready, and work placement is a core module in Year 3. Students will complete a work placement from spring until August.

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

Skills and Careers Information

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

  • Top in salary
  • IBM Predicts Demand for Data Scientists will Soar 28% By 2020 (Forbes, May 2017)
  • IBM Predicts Demand for Data Scientists will Soar 28% By 2020 (Forbes, May 2017)
  • Data science skills (Forbes, May 2017)
  • most challenging to recruit for
  • create the greatest change to products     
  • Top in job satisfaction
  • Demand will only increase

Sectors / Companies currently employing Data Scientists

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 requirement of 2*H5 and 4*O6/H7. 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. 

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