Overview

Course overview

  • Study a master’s in Data Science at a university ranked top 10 in the UK for maths, statistics and computer science (Times Higher Education World University Rankings by Subject, 2025).
  • Study within a uniquely interdisciplinary programme that brings together expertise from across Manchester’s facilities, giving you both strong foundations in the field and the opportunity to collaborate across disciplines to tackle local and global challenges.
  • Gain hands-on experience analysing real-life data using a variety of programming languages for data analysis, including R, Python, and SQL among others.
  • Develop highly desirable professional skills to pursue a career in diverse areas such as policy, business, research and more.
  • Graduate from one of the UK’s most targeted universities by top employers (High Fliers, The Graduate Market Report 2024).
  • Seamlessly transition from master's to PhD study through a fully-funded 1+3 pathway with our prestigious ESRC North West Social Sciences Doctoral Training Partnership (NWSSDTP).
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Explore the new MSc in Data Science

Open days

Contact details

School/Faculty
School of Social Sciences
Contact name
School of Social Sciences Admissions Office
Telephone
+44 (0) 161 306 5500
Email
Website
https://www.socialsciences.manchester.ac.uk/social-statistics/
School/Faculty overview

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) 

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 units 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

 In your application, you should demonstrate aptitude, knowledge and/or interest in three areas: 

  • data analytics and/or statistics;
  • computational subjects; and
  • pathway specific requirements.

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

Please see our application and selection page for more detailed information.

English language

Applicants whose first language is not English should meet the following language requirements:

  • IELTS Academic test score of 7 overall with no component score below 6.5
  • TOEFL IBT 100 with no score below 22 in each section. TOEFL code for Manchester is 0757
  • Pearson Test of English (PTE) score of 76 overall and no component score below 70

Pre-Sessional English Courses

We will consider applicants who do not meet these scores but you may be required to complete a pre-sessional English language course at the University of Manchester prior to the start of the course.

To be considered for a pre-sessional English language course for this programme we require the following minimum IELTS (Academic) scores:

6 Week Pre-Sessional Course : IELTS 6.5 overall with 6.0 in each sub-skill  

10 Week Pre-sessional Course : IELTS 6.0 overall with 6.0 in three sub-skills, and 5.5 in no more than one sub-skill  

If you have not yet completed your current academic study and are interested in studying a pre-sessional course, you must hold an IELTS for UKVI (Academic) test certificate to ensure that you are eligible for a separate visa for the English language 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.

Applicants from Majority English-speaking countries

If you are a national of a   majority English-speaking country   (or have studied for a full bachelor's degree or higher from one of these countries) you may be exempt from submitting further evidence of English language proficiency.

Fees and funding

Fees

For entry in the academic year beginning September 2026, the tuition fees are as follows:

  • MSc (full-time)
    UK students (per annum): £17,300
    International, including EU, students (per annum): £35,200

Further information for EU students can be found on our dedicated EU page.

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

For information on available scholarships please visit: Master’s Fees and Funding

Application and selection

How to apply

Staged admissions

In your application, you should demonstrate aptitude, knowledge and/or interest in three areas:

  • data analytics and/orstatistics;
  • computationalsubjects;
  • pathway specific requirements.

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

Staged Admissions

As there is a high demand for our courses, we operate a staged admissions process with selection deadlines throughout the year. Due to the competition for places and high quality of applications that we receive, we give preference to students from high ranking institutions and with grades above our minimum entry requirements.

Please ensure you submit all supporting documentation with your application to avoid a delay in processing.

Applications for 2026 entry:

Stage 1: Application received by 7th December 2025 ; Application update by 20th February 2026

Stage 2: Application received by 1st March 2026 ; Application update by 1st May 2026

Stage 3: Application received by 3rd May 2026 ; Application update by 19th June 2026

Stage 4: Application received by 5th July 2026 ; Application update by 31st July 2026

Whilst we aim to give you a decision on your application by the deadline date, in some instances due to the competition for places and the volume of applications received, it may be necessary to roll your application forward to the next deadline date.

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

Please note: All places are subject to availability and if you apply at one of the later stages, some courses may already be reaching capacity or be closed to further applications. We, therefore, recommend that you apply early in the cycle to avoid disappointment.

Course details

Course description

The inexorable rise of the digital world, driven by rapid AI development, has made data scientists more in demand right now than ever before. The advances of analysing big data span beyond the digital and technology industry and are increasingly recognised in the worlds of sport, medicine, space exploration and more. Our MSc Data Science (Social Analytics) course prepares you for a successful career in this high-demand field.

You’ll develop invaluable abilities in key area’s such as:

  • data analysis;
  • project design;
  • computational methods;
  • data stewardship.

See a full list of mandatory and optional course units below.

If you’re looking to specialise in the technical and computational side of data science our course is well-suited to meet your needs. You will focus on the data techniques and uses that are most relevant to social analytics.

We welcome applicants from a range of STEM, business and humanities backgrounds, allowing us to create a diverse cohort and enrich discussions around the uses and potential of data.

By the end of your studies, you will have developed a highly valued skillset, enhancing your employability across countless sectors such as policy, business, research and more. Previous students have gone on to roles such as data scientists, civil servants, consultants, researchers, entrepreneurs, and in AI.

This course is eligible for the 1+3 studentship offered by the Economic and Social Sciences Research Council (ESRC) North West Social Sciences Doctoral Training Partnership (NWSSDTP), offering a unique, fully-funded route into postgraduate research. If your application is successful, you’ll be able to seamlessly transition from master's-level study to a PhD. Find out more on our 1+3 ESRC NWSSDTP webpage.

Aims

This course will:

  • Provide an opportunity for graduates from a broad range of disciplines to develop data science skills.
  • Train you to ask important research questions, evaluate the quality of available evidence, select appropriate methods and use analytical skills to visualise, interpret and provide strategic advice and insight.
  • Enable you to develop into an agile, skilled data scientist adept at working in a variety of settings, able to meet the challenges and rewards of interdisciplinary teamwork.

Special features

Interdisciplinary approach

Gain a comprehensive understanding of data analytics through studying varied aspects and applications of data science from Statistics, Demography, Social Networks, Data Science, Economics, Politics, Criminology, Health, Sociology, and other fields.

Hands-on

Make theory come alive with hands on experience analysing real-world data using a variety of statistical software such as R, Python, Excel and more.

Teaching and learning

This course is taught by an interdisciplinary team using a variety of delivery methods:

  • lectures;
  • computer based practicals;
  • e-learning;
  • workshops;
  • student presentations;
  • group work;
  • individual research.

Coursework and assessment

Course units are assessed in a variety of ways, including:

  • exams;
  • essays;
  • reports;
  • online tests;
  • video and in person presentations;
  • presenting code files;
  • group work;
  • practical skills assessments.

Course unit details

A master’s degree is formed of 180 credits.

120 of these credits are made up by a mix of mandatory and optional course units, worth 15 credits each. You will need to select eight of these course units, with 60 credits taken each semester.

The core units are:

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

Optional course units range from statistical foundations to social network modelling and policy inferences, preparing you with a varied but strong foundation in data and social analytics.

The availability of individual optional course units may be subject to change. Information that is sent to you in August about registration onto the course will clearly state the course units that are available in the academic year ahead.

The remaining 60 credits are awarded through a compulsory research component in the form of a 8500-word extended research project. Your project will mirror a real-world data science investigation, including replication code and an accompanying overview video for stakeholders. Your dissertation must be within the area of one of the course units you have chosen.

Your extended research project is supported by weekly research methodology lectures designed to improve your academic, research and writing skills.

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
DATA70121 15 Mandatory
DATA70132 15 Mandatory
DATA70141 15 Mandatory
DATA70202 15 Mandatory
DATA71011 15 Mandatory
DATA72000 60 Mandatory
DATA70302 15 Optional
DATA70402 15 Optional
PLAN60761 15 Optional
SOCY60361 15 Optional
SOST60421 15 Optional
SOST70022 15 Optional
SOST70042 15 Optional
SOST70172 15 Optional
SOST71032 15 Optional
Displaying 10 of 15 course units

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 University of Manchester is one of the most targeted universities by the UK’s top graduate employers (High Fliers, The Graduate Market Report 2024).

This innovative MSc in Data Science provides you with the data skills required for a range of careers within:

  • banking and financial services;
  • charities and research organisations;
  • The Civil Service;
  • the IT and tech sector;
  • business management;
  • high performance sports analysis;
  • large retail chains;
  • the pharmaceutical industry.

Many students also choose to continue specialising for a career in research and universities through a PhD at Manchester, or another leading institution, preparing for a career in research or academia.

The University has its own dedicated, award-winning Careers Service where you can benefit from tailored careers support, practice interviews, CV and application support, job listings for Manchester students, and much more. Better yet, you will have access to our Careers Service both during your course and for two years after you graduate, so we know you’re on the right path.

Regulated by the Office for Students

The University of Manchester is regulated by the Office for Students (OfS). The OfS aims to help students succeed in Higher Education by ensuring they receive excellent information and guidance, get high quality education that prepares them for the future and by protecting their interests. More information can be found at the OfS website.

You can find regulations and policies relating to student life at The University of Manchester, including our Degree Regulations and Complaints Procedure, on our regulations website.