Data Science & Analytics (BSc (Hons))

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2. Undergraduate
3. Courses
4. Data Science and Analytics

About This Course

Explore This Section

Fact File

• Title

  Data Science & Analytics

• Code

  CK411

• College

  Science, Engineering and Food Science

• Duration

  4 years

• Teaching Mode

  Full-time

• Qualifications

  BSc (Hons)

• Fees

  Student Contribution + Capitation: €3,138 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

  2022: 467

• CAO Points Range

  467-625

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.

Our BSc in Data Science & Analytics degree at UCC provides education in data storage, manipulation and interpretation using mathematical sciences and computational methods which assists us in solving 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 the Spring of third year, you undertake a six-month work placement (paid in most cases) providing an opportunity to apply the knowledge you have learned in a workplace environment. In the fourth year, you choose specialised modules and undertake an independent project, which enables you 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

All modules 5 credits unless otherwise stated.

• CS1106 Introduction to Relational Databases
• CS1112 Foundations of Computer Science I
• CS1113 Foundations of Computer Science II 
• CS1117 Introduction to Programming (15 credits)
• AM1054 Mathematical Software 
• MA1058 Introduction to Linear Algebra
• MA1059 Calculus 
• ST1050 Statistical Programming in R
• ST1051 Introduction to Probability and Statistics

Plus 5 credits from the following:

Electives

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

Year 2 (Core)

• CS2208 Information Storage and Management I 
• CS2209 Information Storage and Management II 
• CS2513 Intermediate Programming
• CS2514 Introduction to Java 
• CS2515 Algorithms and Data Structures I
• CS2516 Algorithms and Data Structures II 
• MA2055 Linear Algebra 
• MA2071 Multivariable Calculus
• ST2053 Introduction to Regression Analysis
• ST2054 Probability and Mathematical Statistics (10 credits)

Electives

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

Year 3 

• CS3204 Cloud Infrastructure and Services
• CS3205 Data Visualization for Analytics Applications 
• CS3220 Work Placement DSA (10 credits) 
• CS3306 Workplace Technology and Skills (10 credits)
• CS3318 Advanced Programming with Java 
• CS3509 Theory of Computation 
• ST3053 Stochastic Modelling I 
• ST3061 Statistical Theory of Estimation 
• ST3069 Generalised Linear Models 
• ST3070 Statistical Theory of Hypothesis Testing 
• plus Work placement: 6 months (March to September) or 12 months (from March)

Year 4 

• CS4701 Analytics Project for Computer Science (15 credits) or
• ST4092 Data Analytics Project (15 credits)

and

• CS4704 Algorithms and Data Structures for Analytics
• CS4705 Computational Machine Learning 
• ST4060 Statistical Methods for Machine Learning I
• ST4061 Statistical Methods for Machine Learning II
• ST4069 Multivariate Methods for Data Analysis (10 credits)

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

The degree is jointly offered by the School of Computer Science and Information Technology and the Department of Statistics, UCC 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 academic staff member and an employee of the company.

Skills and Careers Information

The World Economic Forum predicts that by 2022, data scientists and analysts will become the number one emerging role in the world. Data science experts are needed in virtually every job sector, not just technology. In the US, the average data scientist salary is US$113,000, according to Glassdoor. (World Economic Forum 2020)

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

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

Mature Students: Find out about the mature entry requirements here.

Fees and Costs

Course fees include a tuition fee, student contribution fee and capitation fee. The state will pay the tuition fees for EU students who are eligible under the Free Fees Scheme. The annual student Contribution and Capitation Fees are payable by the student. In 2022/23the Student Contribution Fee will be €3,000 and the Capitation Fee will be €138.

Please see Fees Office for more information.

How Do I Apply

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.

Our BSc in Data Science & Analytics degree at UCC provides education in data storage, manipulation and interpretation using mathematical sciences and computational methods which assists us in solving 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 the Spring of third year, you undertake a six-month work placement (paid in most cases) providing an opportunity to apply the knowledge you have learned in a workplace environment. In the fourth year, you choose specialised modules and undertake an independent project, which enables you 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

All modules 5 credits unless otherwise stated.

• CS1106 Introduction to Relational Databases
• CS1112 Foundations of Computer Science I
• CS1113 Foundations of Computer Science II 
• CS1117 Introduction to Programming (15 credits)
• AM1054 Mathematical Software 
• MA1058 Introduction to Linear Algebra
• MA1059 Calculus 
• ST1050 Statistical Programming in R
• ST1051 Introduction to Probability and Statistics

Plus 5 credits from the following:

Electives

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

Year 2 (Core)

• CS2208 Information Storage and Management I 
• CS2209 Information Storage and Management II 
• CS2513 Intermediate Programming
• CS2514 Introduction to Java 
• CS2515 Algorithms and Data Structures I
• CS2516 Algorithms and Data Structures II 
• MA2055 Linear Algebra 
• MA2071 Multivariable Calculus
• ST2053 Introduction to Regression Analysis
• ST2054 Probability and Mathematical Statistics (10 credits)

Electives

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

Year 3 

• CS3204 Cloud Infrastructure and Services
• CS3205 Data Visualization for Analytics Applications 
• CS3220 Work Placement DSA (10 credits) 
• CS3306 Workplace Technology and Skills (10 credits)
• CS3318 Advanced Programming with Java 
• CS3509 Theory of Computation 
• ST3053 Stochastic Modelling I 
• ST3061 Statistical Theory of Estimation 
• ST3069 Generalised Linear Models 
• ST3070 Statistical Theory of Hypothesis Testing 
• plus Work placement: 6 months (March to September) or 12 months (from March)

Year 4 

• CS4701 Analytics Project for Computer Science (15 credits) or
• ST4092 Data Analytics Project (15 credits)

and

• CS4704 Algorithms and Data Structures for Analytics
• CS4705 Computational Machine Learning 
• ST4060 Statistical Methods for Machine Learning I
• ST4061 Statistical Methods for Machine Learning II
• ST4069 Multivariate Methods for Data Analysis (10 credits)

Recognised Qualification

Tawjihiyah (General Secondary Education Certificate) PLUS 1 Year at Bachelor degree level from a recognised university with competitive grades in specific relevant subjects

Band 2 Programmes

Minimum Entry Requirements

Minimum average of 90% in Tawjihiyah (General Secondary Education Certificate) PLUS competitive grades in year 1 at Bachelor degree level.

International Baccalaureate   

1. Study
2. Undergraduate
3. Courses
4. Data Science and Analytics

About This Course

Explore This Section

Fact File

• Title

  Data Science & Analytics

• Code

  CK411

• College

  Science, Engineering and Food Science

• Duration

  4 years

• Teaching Mode

  Full-time

• Qualifications

  BSc (Hons)

• Fees

  Student Contribution + Capitation: €3,138 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

  2022: 467

• CAO Points Range

  467-625

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.

Our BSc in Data Science & Analytics degree at UCC provides education in data storage, manipulation and interpretation using mathematical sciences and computational methods which assists us in solving 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 the Spring of third year, you undertake a six-month work placement (paid in most cases) providing an opportunity to apply the knowledge you have learned in a workplace environment. In the fourth year, you choose specialised modules and undertake an independent project, which enables you 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

All modules 5 credits unless otherwise stated.

• CS1106 Introduction to Relational Databases
• CS1112 Foundations of Computer Science I
• CS1113 Foundations of Computer Science II 
• CS1117 Introduction to Programming (15 credits)
• AM1054 Mathematical Software 
• MA1058 Introduction to Linear Algebra
• MA1059 Calculus 
• ST1050 Statistical Programming in R
• ST1051 Introduction to Probability and Statistics

Plus 5 credits from the following:

Electives

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

Year 2 (Core)

• CS2208 Information Storage and Management I 
• CS2209 Information Storage and Management II 
• CS2513 Intermediate Programming
• CS2514 Introduction to Java 
• CS2515 Algorithms and Data Structures I
• CS2516 Algorithms and Data Structures II 
• MA2055 Linear Algebra 
• MA2071 Multivariable Calculus
• ST2053 Introduction to Regression Analysis
• ST2054 Probability and Mathematical Statistics (10 credits)

Electives

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

Year 3 

• CS3204 Cloud Infrastructure and Services
• CS3205 Data Visualization for Analytics Applications 
• CS3220 Work Placement DSA (10 credits) 
• CS3306 Workplace Technology and Skills (10 credits)
• CS3318 Advanced Programming with Java 
• CS3509 Theory of Computation 
• ST3053 Stochastic Modelling I 
• ST3061 Statistical Theory of Estimation 
• ST3069 Generalised Linear Models 
• ST3070 Statistical Theory of Hypothesis Testing 
• plus Work placement: 6 months (March to September) or 12 months (from March)

Year 4 

• CS4701 Analytics Project for Computer Science (15 credits) or
• ST4092 Data Analytics Project (15 credits)

and

• CS4704 Algorithms and Data Structures for Analytics
• CS4705 Computational Machine Learning 
• ST4060 Statistical Methods for Machine Learning I
• ST4061 Statistical Methods for Machine Learning II
• ST4069 Multivariate Methods for Data Analysis (10 credits)

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

The degree is jointly offered by the School of Computer Science and Information Technology and the Department of Statistics, UCC 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 academic staff member and an employee of the company.

Skills and Careers Information

The World Economic Forum predicts that by 2022, data scientists and analysts will become the number one emerging role in the world. Data science experts are needed in virtually every job sector, not just technology. In the US, the average data scientist salary is US$113,000, according to Glassdoor. (World Economic Forum 2020)

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

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

Mature Students: Find out about the mature entry requirements here.

Fees and Costs

Course fees include a tuition fee, student contribution fee and capitation fee. The state will pay the tuition fees for EU students who are eligible under the Free Fees Scheme. The annual student Contribution and Capitation Fees are payable by the student. In 2022/23the Student Contribution Fee will be €3,000 and the Capitation Fee will be €138.

Please see Fees Office for more information.

How Do I Apply

Please note you will be required to provide additional information as part of the online application process for this programme. This will include the following questions:

• You may enter the details of professional or voluntary positions held. We strongly encourage you to complete this section with all relevant work experiences that will support your application.

• In addition to your previously declared qualifications, please outline any additional academic courses, self-learning and professional training relevant to this programme.

• Please describe your motivation and readiness for this programme.