MSc Data Science 2018/19 entry

Duration Full time 1 year
Discipline
  • Computer Science
LocationExeter (Streatham)
Start date September

Overview

Data Science at the University of Exeter

MSc Data Science is an inter-disciplinary course aimed at students wishing to work in data science – a field with almost limitless career potential. Teaching covers the fundamental mathematical and computational techniques used to deliver insights and understand phenomena extracted from data sources. Building upon your existing coding skills you will handle complex data sets, learning multiple methods of analysis and efficient approaches to visualisation and presentation.

As well as specific applications including network analysis, text analysis and machine vision you will study social contexts, governance and ethical considerations.

Your project allows you to develop skills in an area of interest, pursuing your ideas while guided by an academic supervisor.

Programme structure 2018/19

Please note: the modules and structure of this course are currently in development. The following is an indicative list only and remains subject to change.

Code

Title

Credits

Compulsory modules

ECMM4xx

Introduction to Data Science

This module is still in development but will be similar to ECMM429

15

ECMM4xx

Fundamentals of Data Science

This module is still in development but will be similar to ECMM430

15

ECMM4xx

Learning From Data

This module is still in development but will be similar to ECMM420

15

ECMM422

Machine Learning

15

ECMM4xx

Data Science Research Project

60

Optional modules

Select 45 credits from the options below. Some statistics modules require suitable background knowledge as a prerequisite.

ECMM410

Research Methodology

15

ECMM409

Nature Inspired Computation

15

TBC

Bayesian Statistics

This module is still in development but will be similar to ECM3741

15

ECMM733

Statistical Modelling in Space and Time

15

TBC

Social Networks and Text Analysis

This module is still in development but will be similar to ECMM439

15

ECMM423

Evolutionary Computation & Optimisation

15

ECMM426

Computer Vision

15

TBC

High Performance Computing and Distributed Systems

This module is still in development but will be similar to ECM3426

15

TBC

Digital Business Models

This module is still in development

15

TBC

Advanced Statistical Modelling

This module is still in development but will be similar to ECM3712

15

TBC

Stochastic Processes

This module is still in development but will be similar to ECM3724

15

You may choose up to 30 credits of NQF Level 7 modules which are not listed above, either from within or outside the College of Engineering, Mathematics and Physical Sciences, subject to approval, timetabling and satisfaction of prerequisites.

The modules we outline here provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.

Learning and teaching

Teaching is mainly delivered by lectures, workshops and online materials. Each module references core and supplementary texts, or material recommended by module deliverers, which provide in depth coverage of the subject and go beyond the lectures.

We believe every student benefits from being taught by experts active in research and practice. All our academic staff are active in internationally-recognised scientific research across a wide range of topics. You will discuss the very latest ideas, research discoveries and new technologies, becoming actively involved in a research project yourself.

We aim to provide a supportive environment where students and staff work together in an informal and friendly atmosphere. The department has a student-focused approach to teaching, whereby all members of staff deal with questions on an individual basis. We operate an open door policy, so it is easy to consult individual members of staff or to fix appointments with them via email. As a friendly group of staff, you will get to know us well during your time here.

The assessment strategy for each module is explicitly stated in the full module descriptions given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills. Assessment methods include essays, closed book tests, exercises in problem solving, use of the Web for tool-based analysis and investigation, mini-projects, extended essays on specialized topics, and individual and group presentations.

Careers

“The Sexiest Job of the 21st Century.” - Harvard Business Review

Data Science is changing the way people do business. Mountains of previously uncollectable data, generated by huge growth in online activity and appliance connectivity, is becoming available to businesses in every sector. The opportunities for businesses and individuals who can manage, manipulate and extract insights from these enormous data sets are limitless. A direct result of this is the dramatic increase in demand for individuals with the skills to turn this information into insight is outstripping supply.

Whether you’re looking to take your career in a new direction or for an MSc that will sit alongside your undergraduate degree to land you an exhilarating graduate job, you’re unlikely to find a better choice than Data Science.

Entry requirements 2018/19

Candidates will be required to have at least a 2:1 degree in a numerate subject, and must be able to show evidence of good programming ability in recognised modern computer languages.

Candidates may be interviewed by video conference to assess their programming ability and suitability for the course.

Requirements for international students

If you are an international student, please visit our international equivalency pages to enable you to see if your existing academic qualifications meet our entry requirements.

English language requirements

IELTS (Academic)

Overall score 6.5. No less than 6.0 in any section.

TOEFL IBT*

Overall score 90 with minimum scores of 21 for writing, 21 for listening, 22 for reading and 23 for speaking.

Pearson Test of English (Academic)

58 with no less than 55 in all communicative skills.

Cambridge English: Advanced & Proficiency

Overall score 176. No less than 169 in any section.

Pre-sessional English

Applicants with lower English language test scores may be able to take pre-sessional English at INTO University of Exeter prior to commencing their programme. See our English language requirements page for more information.

Fees and funding 2018/19

Tuition fees per year 2018/19

  • UK/EU: £10,000 full-time; £5,000 part-time
  • International: £23,000 full-time

Fee information

Fees can normally be paid by two termly instalments and may be paid online. You will also be required to pay a tuition fee deposit to secure your offer of a place, unless you qualify for exemption. For further information about paying fees see our Student Fees pages.

UK government postgraduate loan scheme

Postgraduate loans of up to £10,000 are now available for Masters degrees. Find out more about eligibility and how to apply.

Global Excellence Scholarship

We are delighted to offer Global Excellence Scholarships for students of outstanding academic quality applying to postgraduate Taught programmes starting in autumn 2018.

Contact us

We welcome enquiries about the course.

For further information contact:

Web: Enquire online
Phone: +44 (0) 1392 724061