Smart and Resilient Cities MSc

This course is in clearing

Why study at UEL?

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Overall Positivity*, National Student Survey 2026

Fastest Rising in England for graduate employability

Graduate Outcomes Survey 2025

Overview

Course modules

Over one year, you will explore how data, artificial intelligence and digital technologies can support sustainable and resilient urban development. In Semester A, you will study the foundations of sustainable, smart and resilient cities alongside the fundamentals of artificial intelligence. In Semester B, you will develop advanced skills in urban data science and machine learning on big data. In the final stage, you will complete an independent dissertation addressing a specialist challenge related to smart and resilient cities.

NOTE: Modules are subject to change. For those studying part time courses the modules may vary.

Entry requirements

MSc:

What makes this course different

Real-world urban data

Work with real-world or simulated urban datasets to investigate challenges in areas such as transport, environment, health, infrastructure and planning.

Technology for urban change

Apply artificial intelligence, machine learning, urban analytics and digital technologies to develop data-driven solutions for sustainable and resilient cities.

Careers with impact

Prepare for careers in urban data science, smart-city innovation, digital infrastructure and sustainability across public, private and civic technology sectors.

Course options

Start date

MSc

Smart and Resilient Cities MSc, home applicant, full time

  • Home Applicant ,
  • Full time, 1 year
  • £ 11,940 per year

Smart and Resilient Cities MSc, home applicant, part time

  • Home Applicant ,
  • Part time, 2 years
  • £ 1,990 per 30 credits

What we’re researching

Our academic team undertakes research across artificial intelligence, data science, urban analytics, digital infrastructure, sustainability and resilient systems. This research informs teaching in areas such as machine learning, spatial and temporal data analysis, decision support, responsible innovation and the use of digital technologies to address complex societal challenges. Students may have opportunities to develop dissertation topics connected to staff expertise and current research themes.

Your future career

The standard MSc does not include a compulsory placement. Students who choose the two-year MSc with Industrial Placement route undertake a placement after successfully completing the taught modules and dissertation. Across both routes, applied projects, real-world datasets and industry-informed learning will help you develop professional and technical skills relevant to urban innovation.

Industry links

The course will draw on UEL’s wider engagement with local authorities, public-sector organisations, technology companies, sustainability specialists and urban innovation networks. Students may benefit from industry-informed projects, guest speakers, applied case studies and opportunities to work with real-world urban datasets. Specific partners and activities may vary from year to year.

Graduate employers

Graduates may pursue opportunities across a wide range of organisations and sectors, including:

  • Local authorities and government agencies, such as London borough councils, the Greater London Authority and central government departments
  • Urban planning and infrastructure consultancies, such as Arup and AECOM
  • Transport and mobility organisations, such as Transport for London and other public or private transport operators
  • Environmental and sustainability consultancies
  • Technology and data analytics companies
  • Public health and public-sector data services, including NHS organisations and health analytics teams
  • Civic technology and smart-city start-ups
  • International development organisations working on sustainable urban development and resilience

Job roles

Graduates from this course will be equipped for a wide range of roles at the intersection of technology, data and urban development. Key job titles include:

  • Smart-city analyst
  • Urban data scientist
  • GIS or spatial-data analyst
  • Sustainability data analyst
  • Digital transformation analyst
  • Urban innovation officer
  • Smart-infrastructure analyst
  • Resilience or sustainability consultant
  • Research or policy analyst

Further study

Graduates from MSc Smart and Resilient Cities may choose to progress to further postgraduate research, with MRes and PhD options available

How you'll learn

Learning is practical, applied and collaborative. You will take part in lectures, laboratory sessions, workshops, seminars and guided project work. Activities may include urban data analysis, spatial and temporal modelling, artificial intelligence exercises, case-study evaluation, dashboard development and scenario-based problem-solving using real or simulated urban datasets.

Early practical sessions will provide structured guidance, while later activities will support you in working more independently on complex urban challenges. You will also undertake independent study, including directed reading, preparation for practical activities, coursework development and dissertation research.

The standard MSc does not include a compulsory placement. Students who choose the MSc Smart and Resilient Cities with Industrial Placement route will undertake a placement after successfully completing all taught modules and the dissertation. The University provides guidance and employability support, but students are responsible for securing a suitable placement, and placements are competitive and not guaranteed.

Guided independent study

When not attending timetabled lectures or workshops, you will be expected to continue learning independently through self-study. This will typically involve skills development through online study, reading journal articles and books, working on individual and group projects and preparing coursework assignments and presentations.

Your independent learning is supported by a range of excellent facilities including online resources, and specialist facilities, such as edit suites, the library, the full Microsoft Office software, including MS Teams, and Moodle: our Virtual Learning Environment.

Academic support

Our academic support team provides help in a range of areas - including learning and disability support.

Dedicated personal tutor

When you arrive, we'll introduce you to your personal tutor. This is the member of the academic course team who will provide academic guidance, be a support throughout your time at UEL and who will show you how to make the best use of all the help and resources that we offer.

Your timetable

Across the taught modules, you will normally undertake approximately 252 hours of scheduled lectures, seminars, laboratories, workshops and other student–tutor interaction. Contact patterns may vary between modules, and the dissertation includes additional supervisory support.

Class sizes

As this is a new course, we can't give an indication of class sizes. However, we are predicting an intake of between 10-25 students each year.

How you will be assessed

Assessment is primarily coursework-based and may include individual and group reports, portfolios, applied analytics projects, presentations, practical exercises, quizzes or class tests, and an independent dissertation. There are no traditional end-of-year written examinations.

Students on the industrial placement route are also assessed through a pass/fail training report, reflective diary, development plan and employer-related evidence.

Campus and facilities

What our students and staff say

Fahimeh Jafari
Cities are becoming increasingly complex, and addressing challenges in areas such as transport, sustainability, public services, infrastructure and resilience requires professionals who can combine technical knowledge with an understanding of urban systems. This course brings together artificial intelligence, machine learning, urban data science and sustainable city principles, giving students the opportunity to develop practical, data-driven solutions to real urban challenges.

Dr Fahimeh Jafari

Course Leader