Data Analytics

Overview

Data Analytics is an exciting field of rapid developments. Data is everywhere and continuing to grow massively, creating huge growth in demand for qualified experts to be able to extract the real benefit from the data.



The role of a data scientist is highly diverse overlapping many areas from computer science, to the fundamentals of mathematics, statistics, modelling and analytics while also requiring the right skills to be able to see the detail, solve the problem (having specified the problem!), and communicate effectively the findings to colleagues to empower them to make decisions.



The diversity of data analytics opens up many job opportunities from working in software companies, healthcare, banking, insurance, policing, tech companies to applying your knowledge to intelligent buildings and behaviour analytics of customers.



The programme provides a balanced route to learning through a blend of academic study and lab sessions, with a heavy focus on practical engagement with industry. In the first and second semesters, you will study 6 modules full-time which include opportunities for blended and collaborative learning. In the third semester you will undertake a significant industry based project.



Course Details

The aim of the programme is to offer a multi-disciplinary education in data analytics that prepares graduates with key knowledge, skills and competencies necessary for employment in analytics and data science positions.



In particular, the programme aims to provide students with:

• Comprehensive knowledge and understanding of the fundamental principles of statistics and computer science that underpin analytics.



• Advanced knowledge and practical skills in the theory and practice of analytics.



• The necessary skills, tools and techniques needed to embark on careers in data analytics and data science.



• Skills in a range of practices, processes, tools and methods applicable to analytics in commercial and research contexts.



• Timely exposure to, and practical experience in, a range of current software packages and emerging new applications of analytics.



• Opportunities for the development of practical skills in a commercial context.

Core Modules

• Machine Learning (20 credits)

• Data Mining (20 credits)

• Data Analytics Fundamentals (20 credits)

• Analytics in Action (20 credits)

• Database & Programming Fundamentals (20 credits)

• Frontiers in Analytics (20 credits)

• Individual Industry Based Project (60 credits)

Graduate

Normally a 2.2 Honours first degree in Mathematics, Statistics, or Computer Science or a closely related discipline, or equivalent qualification acceptable to the University.



Applicants with a minimum 2.2 Honours degree in a subject area not fulfilling the discipline criterion above require A Level Mathematics at grade B, or equivalent qualification acceptable to the University, and will be required to pass an aptitude test.

Coursework

Written examination

Project dissertation

1 year (Full-time)

2 years (Part-time)

Entry Year: 2024/25

Career Prospects

Introduction

Industry forecasts indicate that Data Analytics is a growing field internationally, with job opportunities set to increase exponentially predicting growths of 160% between 2013 and 2020 (eSkills report, Big Data Analytics 2013-2020). There is a current shortage in qualified staff for these roles, which is also the case in Northern Ireland where there have been a number of recent investments and expansions in the Data Analytics sector.



The course is designed to meet the needs of Industry where graduates have the right combination of the skills and expertise in both computer science, mathematics and statistics along with the experience they gain in their individual industry based project to be highly sought after for employment.