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(Available from 2018) Data Science and Analytics BSc (Hons)

Fact File

Course Code: CK411

Course Title: Data Science and Analytics

Subject Title: (Available from 2018)

College: Science, Engineering and Food Science

Data Science and Analytics

Duration: 4 years

Qualifications: BSc (Hons)

NFQ Level: Level 8

Costs: The State will pay the tuition fees for full-time EU students who satisfy the Free Fees Criteria. In 2017/18 the Student Contribution Charge will be €3,000 and the Capitation Fee is expected to be €165.

Entry Requirements: H5 in two subjects, and O6/H7 in four other subjects in the Leaving Certificate from Irish, English, Mathematics, and three other subjects recognised for entry purposes. Special Entry Requirements: H3 in Mathematics.

Overview

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 followed by a six-month work placement which provides 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.

Course Details

FIRST YEAR: The first year mathematical sciences modules will provide a solid foundation in applied mathematical modelling, linear algebra, calculus and probability and introductory statistics. The Computer Science modules will provide the foundations of programming, databases and mathematical foundations of computing.

SECOND YEAR: The second year mathematical sciences modules build on the first year modules with more advanced mathematical modelling, linear algebra, calculus, more advanced probability, mathematical statistical and regression methods. These first and second year modules will have a strong applied dimension to them, with extensive use of mathematical and statistical software, especially Mathematica and R. The Computer Science modules will cover more advanced programming and database theory, and introduce algorithm development.

THIRD YEAR: The third year mathematical sciences modules build on the foundational applied mathematics, mathematics and statistics content studied in the first two years. Concentration is on statistical methods – stochastic modelling, statistical theory of estimation and hypothesis testing and generalised linear models. The Computer Science modules will provide additional skills in algorithms and software engineering, and introduce data visualisation. There will be a 6-month work placement to provide students with industrial experience.

FOURTH YEAR: The fourth year mathematical sciences modules will cover statistical machine learning, multivariate methods and computer intensive statistical analytics. Students will also have the opportunity to select modules to allow them more in-depth study of mathematical modelling, advanced optimization and computational mathematical techniques relevant to data science and analytics and further statistical modelling, including time series and survival modelling. The Computer Science modules will provide expertise in big-data management and in machine learning from 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.

Assessment

Written exams take place at the end of Semester 1 and 2 for years 1, 2, and 4. Exams in 3rd year will take place at end of Semester 1 and in the Spring. Not all modules will have formal examinations. Many modules use other types of assessment including in-class tests, laboratory assignments and project work.

Who Teaches This Course

Lecturers for the Schools of Computer Science and Mathematical Sciences. Staff in both schools are very research active and have leadership roles in:

• Insight Centre for Data Analytics
• Lero Software Research Centre
• Connect Centre for Future Networks and Communications

Further Contact Information

Programme Coordinator 1: Professor Gregory Provan
Email: g.provan@cs.ucc.ie
Telephone: 021 4205928
Address: Room 1-71, Western Gateway Building, University College Cork

Programme Coordinator 2: Dr Michael Cronin
Email: m.cronin@ucc.ie
Telephone: 021 4205825
Address: Room 1-47, Western Gateway Building, University College Cork

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