Overview

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Course overview

Apply data science techniques to understand and address complex urban challenges.

  • Prepare for careers in policy, business and data-driven industries through training in data analysis, computational methods and data stewardship.
  • Join a uniquely interdisciplinary department that develops and applies data-driven insights to the fields of urban and regional planning, policy analysis and design, property, real estate finance and beyond.
  • 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)

For this pathway, we would expect applicants to evidence an interest and/or experience in topics related to urban analysis. Examples are:

  • Working experience in urban-themed topics (e.g. data analyses for spatial phenomena, public policies or real estate market analysis)
  • Experience in working in spatial or GIS-based data analysis
  • Evidence of training in urban-themed methods or topics (e.g. GIS).

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.

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

Cities face growing challenges, from sustainability and transport to housing and population change. 91Ö±²¥ MSc Data Science and Artificial Intelligence (Urban Analytics pathway) and use data science to uncover insights that help create smarter, more resilient urban environments.

The rise of the digital world has made data scientists more in demand than ever, with data analysis now transforming decisions far beyond the tech industry. This interdisciplinary master's course combines core data science training with specialist knowledge in urban analytics.

Throughout your studies, you will build skills in data analysis, project design, computational methods, managing agentic AI, data stewardship, and more.

You will work with real-life data using methodologies and generative AI models, including R, Python and Excel, focusing on uses that are most relevant to urban analytics. Your optional course units will explore themes such as land use, property valuation and town planning, helping you understand how data informs planning, development and policy decisions.

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, opening doors across sectors such as policy, business and research.

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

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

  • lectures;
  • computer based practicals;
  • workshops;
  • online courses and surgeries;
  • meetings with industry partners;
  • Master in Geographical Modelling (online workshops developed with a consortium of European Universities)
  • on-site inspection, measurement and valuation exercise;
  • group work;
  • individual research.

Coursework and assessment

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

  • exams;
  • essays;
  • reports;
  • online tests;
  • group valuation and measurement exercises,
  • 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 (Urban Analytics pathway), there are six mandatory course units, including an extended research project worth 60 credits. This project is a compulsory research component and would include either a technical report or an academic paper on your project, its methods, and outcomes. You would present the aims and results of your project with either a video or a slide deck.

You will also choose three optional course units, which range from statistical foundations to data analysis and GIS, preparing you with a varied and strong foundation in data and urban 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 in Data Science and Artificial Intelligence (Urban 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:

  • urban planning;
  • banking and financial services;
  • transport and logistics;
  • international development agencies and funders;
  • the Civil Service;
  • the IT and tech sector;
  • high-performance sports analysis;
  • large retail chains;
  • the pharmaceutical industry.

You will develop specialist knowledge of urban analytics and its applications to planning, land use and property. Our graduates have progressed into roles such as data scientists, civil servants, consultants, researchers, entrepreneurs and positions within AI-related fields.

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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