Data Science MSci/BSc (Hons)

Program Overview

Course Overview

The course brings together a range of techniques that the modern data scientist needs. You will study modules in mathematics, data analysis and computing, and tackle a variety of interesting and engaging problems from the latest research studies, business and industry.

Why You Should Study This Course

• You will have the chance to equip yourself with transferable and professional skills which prepare you for employment in industry, business, or education.
• You will be provided with the opportunity to develop critical and reflective skills required for problem-solving in a variety of contexts.
• The course has a particular emphasis on modern applications and the use of appropriate computational methods, software and technology.
• You can expect to improve your knowledge and understanding of the theory and practice of the latest data science, as well as the use of computational methods.
• You will have the chance to gain industry-relevant experience as you apply real-world, commercial software development practices within teams of your peers, preparing you for your career after graduation.

What You'll Study

Year One

• Calculus - 20 credits
• Algebra - 20 credits
• Programming: Concepts and Algorithms - 20 credits
• Working with Data - 20 credits
• Programming: Professional Practice - 20 credits
• Probability and Statistics - 20 credits

Year Two

• Artificial Intelligence - 20 credits
• Linear Algebra and Differential Equations - 20 credits
• Advanced Algorithms - 20 credits
• Data Science - 20 credits
• Linear Statistical Models - 20 credits
• Data Science Group Project - 20 credits

Placement Year

• UK Work Placement - 0 credits
• International Study/Work Placement - 0 credits

Final Year

• Data Visualisation - 20 credits
• Statistical Methods for Data Science - 20 credits
• Machine Learning - 20 credits
• Project Discovery - 20 credits
• Dissertation and Project Artefact - 20 credits

Optional Modules

• Artificial Neural Networks - 20 credits
• Mobile Application Development - 20 credits
• Advanced Topics in Statistics - 20 credits

Additional Year (MSci)

• Artificial Neural Networks - 15 credits
• Machine Learning - 15 credits
• Natural Language Processing - 15 credits
• Big Data Analytics and Data Visualisation - 15 credits
• Data Management Systems - 15 credits
• Modelling and Optimisation Under Uncertainty - 15 credits
• Individual Research Project Preparation - 15 credits
• Individual Research Project - 15 credits

How You'll Learn

Learning will be facilitated through a variety of methods which may include lectures, seminars, lab, workshops, online activities and group work.

Teaching Contact Hours

As a full-time undergraduate student, you will study modules totalling 120 credits each academic year. A typical 20 credit module requires a total of 200 hours study.

Assessment

This course will be assessed using a variety of methods which will vary depending upon the module. Assessment methods may include:

• Formal examinations
• Phase tests
• Essays
• Group work
• Presentations
• Reports
• Projects
• Coursework
• Exams
• Individual assignments

Entry Requirements

• UK: 120 UCAS points (BSc), 128 UCAS points (MSci)
• International: 29 points to include 5 points in Mathematics at Higher Level (BSc), 31 points to include 5 points in Mathematics at Higher Level (MSci)
• GCSE: Maths and English at grade 4/C or Functional Skills Level 2
• BTEC: Considered on an individual basis
• Access to HE: Considered on an individual basis

Fees and Funding

• UK: £9,535 per year (BSc), £19,850 per year (MSci)
• International: £19,850 per year
• EU: £9,535 per year with EU Support Bursary, £19,850 per year without EU Support Bursary

Facilities

• The sigma centre provides a wide range of learning resources dedicated to mathematics and statistics.
• Informal Study Areas: Informal computer access to all the specialist software required for your studies.

Careers and Opportunities

• Data analysts have job prospects in areas such as business analysis, risk analysis, energy demand forecasting, health analytics, sports analytics, web analytics, games data analytics, social media analytics and more.
• Previous students have found employment as Financial Analysts at IBM, Gaming Financial Analysts for Warner Bros, Finance Assistants at Scottish Power, Business Performance Process Analysts at National Grid, Power Analysts at E.ON and Customer Service Analysts for Cummins.