Overview

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Course overview

Use data science to understand social behaviour, evidence and change.

  • 91Ö±²¥ within a uniquely interdisciplinary department that develops and applies data-driven insights across statistics, demography, social networks, economics, politics, sociology, and beyond.
  • Work with real-life data using methodologies and generative AI models, including R, Python and Excel, to examine current social challenges such as AI’s impact on workforce, social inequality, conflicts, and threats to democracy.
  • 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).
  • 91Ö±²¥ Data Science and Artificial Intelligence at a university ranked Top 10 in the UK for Computer Science (Times Higher Education World University Rankings by Subject, 2026).

Our students. Real experiences. Visit the page to hear from our students as they share what it’s really like to study here

Open days

The University holds regular events throughout the year, including webinars and the annual on-campus Master's Expo, all of which offer the opportunity to find out more about our facilities and courses from our academic and admissions staff.

We also attend a number of education fairs both in the UK and overseas throughout the year.

For more details on how you can meet us, visit our events page: /study/masters/meet-us/

Contact details

School/Faculty
School/Faculty overview

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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 shoulddemonstrate 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 91Ö±²¥ is 0757. From 2026: 5 overall, with no subskill below 4.5

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

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 (PDF document, 91KB).

Scholarships/sponsorships

We know that student finance can be complicated. The links below provide further information to help guide you.

Learn more about - student finance options for UK students.

Learn more about - fees and finance for international students.

Graduates of The University of Manchester and 91Ö±²¥ Metropolitan University can receive a 10% discount on their master's degree tuition fees as part of our 91Ö±²¥ Alumni Loyalty Discount scheme.

Application and selection

How to apply

Apply online

Staged admissions

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 2027 entry:

Stage 1:Application received by6th December 2026; Application update by19th February 2027

Stage 2:Application received by1st March 2027; Application update by2nd May 2027

Stage 3:Application received by4th May 2027; Application update by18th June 2027

Stage 4:Application received by4th July 2027; Application update by30th July 2027

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

How can we use data to better understand society and improve decision-making? 91Ö±²¥ MSc Data Science and Artificial Intelligence (Social Analytics pathway) and apply data science to social questions, policy challenges and interdisciplinary research to uncover evidence that drives change.

Throughout your studies, you will use data science to investigate social issues and support evidence-based decisions. You will build skills in data analysis, project design, computational methods and data stewardship.

You will receive rigorous training in data analysis, project design, computational methods, managing agentic AI, data stewardship, and more.

Your focus will largely be on the data techniques and uses that are most relevant to social analytics, with optional course units exploring themes such as digital traces, texts, network, and platform data. You will gain skills in analysing both conventional survey data and rich, process-produced data.

You will be taught by an interdisciplinary team through lectures, computer-based practicals, e-learning, meetings with industry partners, workshops, group work and individual research.

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.

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.

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.

On the MSc Data Science and Artificial Intelligence (Social Analytics pathway), there are six mandatory course units, including an extended research project worth 60 credits. This project is a compulsory research component of around 8,500-words, including replication code and an accompanying overview video. Your project must be within the area of one of the course units you have chosen and will mirror a real-world data science investigation.

Your research will be supported by weekly methodology lectures designed to improve your academic, research and writing skills.

You will also choose three optional course units, which range from statistical foundations to social-based data analysis and GIS, preparing you with a varied and 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.

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

Career opportunities
The University of Manchester is the most targeted university by the UK’s top graduate employers (High Fliers, The Graduate Market Report 2026).
Our MSc Data Science and Artificial Intelligence (Social Analytics pathway) gives you the specialist knowledge and skills required for a range of careers across the public, private, and third sectors, such as in:

  • banking and financial services;
  • the Civil Service;
  • the IT and tech sector;
  • high-performance sports analysis;
  • large retail chains;
  • the pharmaceutical industry.

You will acquire vital skills relevant to many different sectors and roles, such as data analysis, qualitative and quantitative research design, academic writing, and communication and teamwork. You could also progress to a PhD in Social Statistics at 91Ö±²¥ or another university.

Careers support
At 91Ö±²¥ you will have access to a number of  opportunities to help boost your employability , such as careers fairs, employer presentations, and workshops through the University’s dedicated  . As a student at 91Ö±²¥, you would have full access to this service during your studies and for two years after you graduate.

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