MSc Data Science

Year of entry: 2020

Overview

Degree awarded
Master of Science (MSc)
Duration
1 year full-time
Entry requirements
  • high 2:1 honours degree (or overseas equivalent)

Full entry requirements

How to apply

Apply here

Course options

Full-time Part-time Full-time distance learning Part-time distance learning
MSc Y N N N

Course overview

  • Absorb and focus on data, and what data science can do.
  • Develop your team-working skills, and actively study as part of a dynamic group.
  • Be inspired by what the interdisciplinary course, drawing on five different disciplines, can provide.
Loading
Explore the new MSc in Data Science

Open days

The University holds regular open days, where you will have the opportunity to tour the campus and find out more about our facilities and courses.

On this day, you will find out more about the School of Social Sciences and our resources, and meet academic and admissions staff who will be able to answer any questions you have.

For more information, see open days and visits .

Fees

For entry in the academic year beginning September 2020, the tuition fees are as follows:

  • MSc (full-time)
    UK/EU students (per annum): £9,500
    International students (per annum): £22,500

The fees quoted above will be fully inclusive for the course tuition, administration and computational costs during your studies.

All fees for entry will be subject to yearly review and incremental rises per annum are also likely over the duration of courses lasting more than a year for UK/EU students (fees are typically fixed for international students, for the course duration at the year of entry). For general fees information please visit postgraduate fees .

Self-funded international applicants for this course will be required to pay a deposit of £1,000 towards their tuition fees before a confirmation of acceptance for studies (CAS) is issued. This deposit will only be refunded if immigration permission is refused. We will notify you about how and when to make this payment.

Policy on additional costs

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

Scholarships/sponsorships

We offer a number of postgraduate taught scholarships and merit awards to outstanding applicants and international students.

In addition, the Manchester Alumni Scholarship Scheme offers a £3,000 reduction in tuition fees to University of Manchester alumni who achieved a First class Bachelor's degree and are progressing to a postgraduate taught master's course.

For more information, see fees and funding or search the University's postgraduate funding database .

Contact details

School/Faculty
School of Social Sciences
Contact name
Debra Hau
Telephone
+44 (0) 161 306 7521
Email
Website
https://www.socialsciences.manchester.ac.uk/social-statistics/
School/Faculty

Courses in related subject areas

Use the links below to view lists of courses in related subject areas.

Entry requirements

Academic entry qualification overview

  • high 2:1 honours degree (or overseas equivalent)

English language

Students whose first language or language of instruction is not English may be asked to provide evidence of fluency in English by achieving scores in English language tests, as follows:

  • an overall score of 7 in IELTS, with a minimum of 6.5 in all components; or
  • TOEFL (IBT) score of 100 with a minimum of 26 in all components.
  • TOEFL code for Manchester is 0757.

Please note that CAS statements are issued only when all conditions of the offer have been satisfied, PDF copy of passport received and the offer accepted.

Applicants that do not meet these scores, may be eligible to do a pre-sessional English language course at Manchester (either 6 or 10 weeks), you will be required to successfully complete the course at the required level before you are permitted to register on your academic course.

English language test validity

Some English Language test results are only valid for two years. Your English Language test report must be valid on the start date of the course.

Application and selection

How to apply

Apply here

Advice to applicants

In your application, you should demonstrate aptitude, knowledge and/or interest in three areas:
  • data analytics and/or statistics;
  • computational subjects; or
  • pathway specific requirements.

These can be demonstrated by course units taken at undergraduate level and high school level, or professional experience.

Due to high demand for this course, we operate a staged admissions process with selection deadlines throughout the year, as follows:  

  • 1 November (decision by 8 December, accept offer by 15 January)
  • 7 January (decision by 14 February, accept offer by 16 March)
  • 2 March (decision by 8 April, accept offer by 8 May)
  • 4 May (decision by 1 June, accept offer by 1 July)

If we make you an offer, you will have approximately 4 weeks in which to accept (conditional and un-conditional offers). Any offers not accepted by the deadline will be withdrawn so that an offer can be made to another candidate.

All conditional offer holders will have until 1 August to satisfy the conditions of their offer.

Due to competition for places, we give preference to students with grades above our minimum entry requirements. 

You need to ensure that you submit your supporting documents with your online application as it may delay us processing your application.

Whilst we aim to give you a decision on your application by the decision date, in some instances due to the competition for places, or volume of applications received, it may be necessary to roll your application forward to the next deadline date. If this is the case, we will let you know after the deadline date.

Applications received after our final selection deadline will be considered at our discretion if places are still available.

We can accept your application before you complete your undergraduate studies; please submit your latest transcripts with your online application. 

Please note: 

  • all places are subject to availability and if you apply for one of the later dates, some courses may already be closed, we recommend that you apply early in the cycle to secure your place;
  • meeting the minimum entry requirements does not guarantee an offer;
  • if you are a current undergraduate student at the University of Manchester, you may be eligible to apply via the 'Fast-Track' scheme, email pg-soss@manchester.ac.uk for further information;
  • international applicants who will require a visa to study in the UK can obtain up-to-date information on the latest student visa advice and guidelines.

How your application is considered

All applicants must submit the following:

  • online application form;
  • CV;
  • supporting statement;
  • transcripts of degree; and
  • two references (please ask your referees to scan or email their references to pg-soss@manchester.ac.uk ).

Please note, applications will not be considered if one or more of the above documents are missing.

When assessing your academic record we take into account your grade average (both overall and for courses relating to the above requirements), position in class, references and the standing of the institution where you studied.

Course details

Course description

The range of pathways reflects the interdisciplinary nature of the course and we welcome applications from students with backgrounds in a range of disciplines, including:
  • business and management;
  • health science;
  • social sciences;
  • geography;
  • planning;
  • computer science; and
  • mathematics.

We provide training in core data science skills, embedded in a disciplinary context provided by the pathway, you will develop:

  • computational skills;
  • data analytical skills;
  • data stewardship skills and knowledge; and
  • project design skills.

Aims

This innovative MSc in Data Science course is an opportunity for graduates from a broad range of disciplines to develop data science skills. Our goal is to help you develop into an agile, skilled data scientist, adept at working in variety of settings and able to meet the challenges and reap the rewards of interdisciplinary team work.

The range of pathways reflects the interdisciplinary nature of the course and we welcome applications from students with backgrounds in a range of disciplines including:

  • business and management;
  • health science;
  • social sciences;
  • geography;
  • planning;
  • computer science; and
  • Mathematics.

We provide training in core data science skills, embedded in a disciplinary context provided by the pathway, you will develop:

  • computational skills;
  • data analytical skills;
  • data stewardship skills and knowledge; and
  • Project design skills.

Course unit details

Through a set of core units, you will develop a set of key data science skills.

The core units are:

  • Machine Learning and Statistics (both semesters);
  • Understanding Databases;
  • Understanding Data and their Environment;
  • Applications in Data Science.

There are five pathways through the course:

  • Applied Urban Analytics;
  • Computer Science Data Informatics;
  • Management and Business;
  • Mathematics;
  • Social Analytics.

Each pathway has a defined set of electives and dissertation options.

Applied Urban Analytics

We would expect applicants to evidence an interest and/or experience in topics related to urban analysis. Examples are:

  • work experience in urban-themed topics (eg data analyses for spatial phenomena, public policies or real estate market analysis);
  • experience working in spatial or GIS-based data analysis;
  • evidence of training in urban-themed methods or topics (eg GIS).

Business and Management

We normally expect applicants to hold a degree in a quantitative or computational subject such as mathematics, statistics, management science or economics, physics, engineering or computer science. Applicants with extensive business and management industrial experience combined with an honours degree in a quantitative subject may also be considered for admission.

Computer Science Data Informatics

We require that all applicants have a strong background in computer science reflected, for example, in solid programming and software development skills.

We typically expect a First or strong Upper Second class honours degree, or the overseas equivalent, in computer science, or in a joint degree with at least 50% computer science content. We may consider a lower proportion where a student has performed consistently strongly in their computer science units. Applicants with extensive computer science industrial experience and an honours degree in computer science, or its overseas equivalent, may also be considered for admission.

Mathematics

You are expected to have an undergraduate degree with a substantial amount of mathematics including probability and statistics. As a minimum you should have done calculus or mathematical analysis, linear algebra, two courses in probability and two courses in statistics. A mathematical statistics course may count as one probability and one statistics course depending on the syllabus. If your course is called advanced mathematics or similar, then we need to know how much calculus/linear algebra it contains.

You can have a look at what Manchester students do in the first two years, or refer to the following list for a little more detail:

  • Calculus or Mathematical Analysis (functions of a single and several variables, continuity, derivatives, integrals, Mean Value Theorem, Taylor series expansion, minimisation and maximisation, Lagrange multipliers);
  • Linear Algebra (linear independence, determinant, inverse, eigenvalues and eigenvectors);
  • Probability I (probabilities and conditional probabilities, Bayes Theorem, moments);
  • Probability II (multivariate and conditional distributions, generating functions, Law of Large Numbers and Central Limit Theorem);
  • Statistics I (descriptive statistics, normal, t, chi¿square and F distributions, significance tests);
  • Statistics II (Maximum likelihood estimation, Likelihood ratio tests, simple regression and analysis of variance).
Social Analytics

You are expected to have a degree with a substantial proportion of social science content; as a minimum you should have completed two degree level courses on topics from any of the following: sociology, psychology, anthropology, economics, history, human geography, political science, public health.

The following includes other skills/experience that would increase the chances of being selected:

  • evidence of applying statistical modelling to social sciences;
  • non-academic experience with the application of statistical models to social issues;
  • experience working on public policy issues or similar.

Course unit list

The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.

TitleCodeCredit ratingMandatory/optional
Applied Spatial Analysis for Planning PLAN60761 15 Optional
Survey Research Methods SOST60421 15 Optional
Longitudinal Data Analysis SOST70022 15 Optional
Complex Survey Designs and Analysis SOST70032 15 Optional
Structural Equation and Latent Variable Modelling SOST70042 15 Optional
Multilevel Modelling SOST70292 15 Optional
Social Network Analysis SOST71032 15 Optional

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: dass@manchester.ac.uk

Careers

Career opportunities

The global demand for data scientist talent continues to grow, as a result, our course qualification will provide a strong boost to your employability.

This innovative MSc is an opportunity for graduates from a broad range of disciplines to develop data science skills. Our goal is to help you develop into an agile, skilled data scientist; adept at working in variety of settings and able to meet the challenges and reap the rewards of interdisciplinary team work.

As a data science postgraduate at Manchester, you will have access to a wide range of careers support tailored to your career or further study.

For more information, see careers and employability .